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Data Science Marathon - 120 Projects To Build Your Portfolio

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Free Download Data Science Marathon - 120 Projects To Build Your Portfolio
Last updated 11/2024
Created by Pianalytix • 75,000+ Students Worldwide
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 796 Lectures ( 133h 30m ) | Size: 64.6 GB

Build 120 Projects in 120 Days- Data Science, Machine Learning, Deep Learning (Python, Flask, Django, AWS, Heruko Cloud)
What you'll learn
Real life case studies and projects to understand how things are done in the real world
Implement Machine Learning algorithms, Present Data Science projects to management
Use SciKit-Learn for Machine Learning Tasks
Explore how to deploy your machine learning models.
Have a great intuition of many Machine Learning models
Learn which Machine Learning model to choose for each type of problem
Learn best practices when it comes to Data Science Workflow
Learn to pre process data, clean data, and analyze large data
Learn to use NumPy for Numerical Data
Use Matplotlib to create fully customized data visualizations with Python.
Explore large datasets and wrangle data using Pandas
Learn to use Seaborn for statistical plots
Requirements
Basic knowledge of Data Science
Description
In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights which analysts and business users can translate into tangible business value.More and more companies are coming to realize the importance of data science, AI, and machine learning. Regardless of industry or size, organizations that wish to remain competitive in the age of big data need to efficiently develop and implement data science capabilities or risk being left behind.In This Course, We Are Going To Work On 120 Real World Projects Listed Below:Project-1: Pan Card Tempering Detector App -Deploy On HerokuProject-2: Dog breed prediction Flask AppProject-3: Image Watermarking App -Deploy On HerokuProject-4: Traffic sign classificationProject-5: Text Extraction From Images ApplicationProject-6: Plant Disease Prediction Streamlit AppProject-7: Vehicle Detection And Counting Flask AppProject-8: Create A Face Swapping Flask AppProject-9: Bird Species Prediction Flask AppProject-10: Intel Image Classification Flask AppProject-11: Language Translator App Using IBM Cloud Service -Deploy On HerokuProject-12: Predict Views On Advertisement Using IBM Watson -Deploy On HerokuProject-13: Laptop Price Predictor -Deploy On HerokuProject-14: WhatsApp Text Analyzer -Deploy On HerokuProject-15: Course Recommendation System -Deploy On HerokuProject-16: IPL Match Win Predictor -Deploy On HerokuProject-17: Body Fat Estimator App -Deploy On Microsoft AzureProject-18: Campus Placement Predictor App -Deploy On Microsoft AzureProject-19: Car Acceptability Predictor -Deploy On Google CloudProject-20: Book Genre Classification App -Deploy On Amazon Web ServicesProject 21 : DNA classification for finding E.Coli - Deploy On AWSProject 22 : Predict the next word in a sentence. - AWS - Deploy On AWSProject 23 : Predict Next Sequence of numbers using LSTM - Deploy On AWSProject 24 : Keyword Extraction from text using NLP - Deploy On AzureProject 25 : Correcting wrong spellings - Deploy On AzureProject 26 : Music popularity classification - Deploy On Google App EngineProject 27 : Advertisement Classification - Deploy On Google App EngineProject 28 : Image Digit Classification - Deploy On AWSProject 29 : Emotion Recognition using Neural Network - Deploy On AWSProject 30 : Breast cancer Classification - Deploy On AWSProject-31: Sentiment Analysis Django App -Deploy On HerokuProject-32: Attrition Rate Django ApplicationProject-33: Find Legendary Pokemon Django App -Deploy On HerokuProject-34: Face Detection Streamlit AppProject-35: Cats Vs Dogs Classification Flask AppProject-36: Customer Revenue Prediction App -Deploy On HerokuProject-37: Gender From Voice Prediction App -Deploy On HerokuProject-38: Restaurant Recommendation SystemProject-39: Happiness Ranking Django App -Deploy On HerokuProject-40: Forest Fire Prediction Django App -Deploy On HerokuProject-41: Build Car Prices Prediction App -Deploy On HerokuProject-42: Build Affair Count Django App -Deploy On HerokuProject-43: Build Shrooming Predictions App -Deploy On HerokuProject-44: Google Play App Rating prediction With Deployment On HerokuProject-45: Build Bank Customers Predictions Django App -Deploy On HerokuProject-46: Build Artist Sculpture Cost Prediction Django App -Deploy On HerokuProject-47: Build Medical Cost Predictions Django App -Deploy On HerokuProject-48: Phishing Webpages Classification Django App -Deploy On HerokuProject-49: Clothing Fit-Size predictions Django App -Deploy On HerokuProject-50: Build Similarity In-Text Django App -Deploy On HerokuProject-51: Black Friday Sale ProjectProject-52: Sentiment Analysis ProjectProject-53: Parkinson's Disease Prediction ProjectProject-54: Fake News Classifier ProjectProject-55: Toxic Comment Classifier ProjectProject-56: IMDB Movie Ratings PredictionProject-57: Indian Air Quality PredictionProject-58: Covid-19 Case AnalysisProject-59: Customer Churning PredictionProject-60: Create A ChatBotProject-61: Video Game sales AnalysisProject-62: Zomato Restaurant AnalysisProject-63: Walmart Sales ForecastingProject-64 : Sonic wave velocity prediction using Signal Processing TechniquesProject-65 : Estimation of Pore Pressure using Machine LearningProject-66 : Audio processing using MLProject-67 : Text characterisation using Speech recognitionProject-68 : Audio classification using Neural networksProject-69 : Developing a voice assistantProject-70 : Customer segmentationProject-71 : FIFA 2019 AnalysisProject-72 : Sentiment analysis of web scrapped dataProject-73 : Determining Red Vine QualityProject-74 : Customer Personality AnalysisProject-75 : Literacy Analysis in IndiaProject-76: Heart Attack Risk Prediction Using Eval ML (Auto ML)Project-77: Credit Card Fraud Detection Using Pycaret (Auto ML)Project-78: Flight Fare Prediction Using Auto SK Learn (Auto ML)Project-79: Petrol Price Forecasting Using Auto KerasProject-80: Bank Customer Churn Prediction Using H2O Auto MLProject-81: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)Project-82: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)Project-83: Pizza Price Prediction Using ML And EVALML(Auto ML)Project-84: IPL Cricket Score Prediction Using TPOT (Auto ML)Project-85: Predicting Bike Rentals Count Using ML And H2O Auto MLProject-86: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)Project-87: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)Project-88: Hospital Mortality Prediction Using PyCaret (Auto ML)Project-89: Employee Evaluation For Promotion Using ML And Eval Auto MLProject-90: Drinking Water Potability Prediction Using ML And H2O Auto MLProject-91: Image Editor Application With OpenCV And TkinterProject-92: Brand Identification Game With Tkinter And Sqlite3Project-93: Transaction Application With Tkinter And Sqlite3Project-94: Learning Management System With DjangoProject-95: Create A News Portal With DjangoProject-96: Create A Student Portal With DjangoProject-97: Productivity Tracker With Django And PlotlyProject-98: Create A Study Group With DjangoProject-99: Building Crop Guide Application with PyQt5, SQLiteProject-100: Building Password Manager Application With PyQt5, SQLiteProject-101: Create A News Application With PythonProject-102: Create A Guide Application With PythonProject-103: Building The Chef Web Application with Django, PythonProject-104: Syllogism-Rules of Inference Solver Web ApplicationProject-105: Building Vision Web Application with Django, PythonProject-106: Building Budget Planner Application With PythonProject-107: Build Tic Tac Toe GameProject-108: Random Password Generator Website using DjangoProject-109: Building Personal Portfolio Website Using DjangoProject-110: Todo List Website For Multiple UsersProject-111: Crypto Coin Planner GUI ApplicationProject-112: Your Own Twitter Bot -python, request, API, deployment, tweepyProject-113: Create A Python Dictionary Using python, Tkinter, JSONProject-114: Egg-Catcher Game using pythonProject-115: Personal Routine Tracker Application using pythonProject-116: Building Screen -Pet using Tkinter & CanvasProject-117: Building Caterpillar Game Using Turtle and PythonProject-118: Building Hangman Game Using PythonProject-119: Developing our own Smart Calculator Using Python and TkinterProject-120: Image-based steganography Using Python and pillowsTip: Create A 60 Days Study Plan Or 120 Day Study Plan, Spend 1-3hrs Per Day, Build 120 Projects In 60 Days Or 120 Projects In 120 Days.The Only Course You Need To Become A Data Scientist, Get Hired And Start A New CareerNote (Read This): This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.
Who this course is for
Beginners in Data Science
Homepage
Код:
https://www.udemy.com/course/build-real-world-data-science-projects/




Код:
Rapidgator
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Data Science for Beginners - Python & Azure ML with Projects

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Free Download Data Science for Beginners - Python & Azure ML with Projects
Published 11/2024
Created by Graeme Gordon
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 109 Lectures ( 11h 29m ) | Size: 8.5 GB

Practical Data Science: Machine Learning, AI, Cloud Computing, and Data Analysis in Python and Azure ML
What you'll learn
Hands On Learning of Data Analysis and Manipulation in Python
Understand and Apply Key Statistical Concepts
Visualize Data to Extract Insights using Matplotlib and Seaborn
Develop and Evaluate Machine Learning Models with Python and Azure Machine Learning Studio
Experience with Cloud Computing and Natural Language Processing
Requirements
There are no prerequisites for this course - it's designed for beginners
All you need is a computer, an internet connection, and a willingness to learn
Description
"Data Science for Beginners - Python & Azure ML with Projects" is a hands-on course that introduces the essential skills needed to work in data science. Designed for beginners, this course covers Python programming, data analysis, statistics, machine learning, and cloud computing with Azure. Each topic is taught through practical examples, real-world datasets, and step-by-step guidance, making it accessible and engaging for anyone starting out in data science.What You Will LearnPython Programming Essentials: Start with a foundation in Python, covering essential programming concepts such as variables, data types, functions, and control flow. Python is a versatile language widely used in data science, and mastering these basics will help you perform data analysis and build machine learning models confidently.Data Cleaning and Analysis with Pandas: Get started with data manipulation and cleaning using Pandas, a powerful data science library. You'll learn techniques for importing, exploring, and transforming data, enabling you to analyze data effectively and prepare it for modeling.Statistics for Data Science: Build your knowledge of key statistical concepts used in data science. Topics include measures of central tendency (mean, median, mode), measures of variability (standard deviation, variance), and hypothesis testing. These concepts will help you understand and interpret data insights accurately.Data Visualization: Gain hands-on experience creating visualizations with Matplotlib and Seaborn. You'll learn to make line plots, scatter plots, bar charts, heatmaps, and more, enabling you to communicate data insights clearly and effectively.Practical, Real-World ProjectsThis course emphasizes learning by doing, with two in-depth projects that simulate real-world data science tasks:California Housing Data Analysis: In this project, you'll work with California housing data to perform data cleaning, feature engineering, and analysis. You'll build a regression model to predict housing prices and evaluate its performance using metrics like R-squared and Mean Squared Error (MSE). This project provides a full-cycle experience in working with data, from exploration to model evaluation.Loan Approval Model in Azure ML: In the second project, you'll learn how to create, deploy, and test a machine learning model on the cloud using Azure Machine Learning. You'll build a classification model to predict loan approval outcomes, mastering concepts like data splitting, accuracy, and model evaluation with metrics such as precision, recall, and F1-score. This project will familiarize you with Azure ML, a powerful tool used in industry for cloud-based machine learning.Customer Churn Analysis and Prediction: In this project, you will analyze customer data to identify patterns and factors contributing to churn in a banking environment. You'll clean and prepare the dataset, then build a predictive model to classify customers who are likely to leave the bank. By learning techniques such as feature engineering, model training, and evaluation, you will utilize metrics like accuracy, precision, recall, and F1-score to assess your model's performance. This project will provide you with practical experience in data analysis and machine learning, giving you the skills to tackle real-world challenges in customer retentionMachine Learning and Cloud ComputingMachine Learning Techniques: This course covers the foundational machine learning techniques used in data science. You'll learn to build and apply models like linear regression and random forests, which are among the most widely used models in data science for regression and classification tasks. Each model is explained step-by-step, with practical examples to reinforce your understanding.Cloud Computing with Azure ML: Get introduced to the world of cloud computing and learn how Azure Machine Learning (Azure ML) can simplify model building, deployment, and scaling. You'll explore how to set up an environment, work with data assets, and run machine learning experiments in Azure. Learning Azure ML will prepare you for a cloud-based data science career and give you skills relevant to modern data science workflows.Additional FeaturesUsing ChatGPT as a Data Science Assistant: Discover how to leverage AI in your data science journey by using ChatGPT. You'll learn techniques for enhancing productivity, drafting data queries, and brainstorming ideas with AI, making it a valuable assistant for your future projects.Testing and Practice: Each section includes quizzes and practice exercises to reinforce your learning. You'll have the opportunity to test your understanding of Python, data analysis, and machine learning concepts through hands-on questions and real coding challenges.By the end of this course, you'll have completed practical projects, gained a strong foundation in Python, and developed skills in data science workflows that are essential in today's data-driven world. Whether you're looking to start a career in data science, upskill, or explore a new field, this course offers the knowledge and hands-on experience you need to get started.
Who this course is for
This course is perfect for beginners who are curious about data science and want a hands-on introduction to this exciting field.
It's ideal for students, career changers, and professionals from non-technical backgrounds who are looking to build a solid foundation in data science skills, including Python programming, data analysis, statistics, machine learning and cloud computing.
Homepage
Код:
https://www.udemy.com/course/data-science-for-beginners-python-azure-ml-with-projects/




Код:
Rapidgator
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Data Structure & Algorithm C++ Zero To HERO 2024 + LEETCODE

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Free Download Data Structure & Algorithm C++ Zero To HERO 2024 + LEETCODE
Last updated 10/2024
Created by Ankit Thakran,Harsh Kajla
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 268 Lectures ( 64h 32m ) | Size: 15 GB

Ace the Google, Amazon, Facebook, Microsoft, Netflix coding interviews. Step by step guide for their toughest questions!
What you'll learn
Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications
Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets
Code an implementation of each data structure, so you understand how they work under the covers
Develop your Analytical skills on Data Structure and use then efficiently.
Improve your problem solving skills and become a stronger developer
Learn everything you need to ace difficult coding interviews
Requirements
Basic knowledge of Programming in C++
NO experience with data structures or computer science needed!
Description
Brand new course ready for the 2024 hiring season! Join a course taught by industry experts that have actually worked both at top tech firms. Graduates of this course are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook + other top tech companies.This is the ultimate resource to prepare you for coding interviews. Everything you need in one place!WHAT OUR LEARNERS ARE SAYING:5 STARS - This was an amazing course. I was a beginner in data structures and algorithms, but I have learned so much that I would consider myself intermediate-advanced. For anyone looking to deepen their understanding of these data structures, their implementation, or their real-world use, I completely recommend buying this course.5 STARS - This is the best course on data structure compare to all data structure course .all the topic of data structure has been completed in this course .if anyone want to learn data structure then you can go for it. thank you sir for making this course on udemy5 STARS - I liked this course very much! It clears out your basics quite well and is does totally what Harsh and Ankit claim they'll do. I would recommend this to everyone who wants to learn Data Structures and Algorithms, especially if you had a phobia for coding like I did. I now love coding! All thanks to them.5 STARS - This course is really amazing. instructor is going beyond and beyond each and every thing was my beyond expectations. really mastery course it is.5 STARS - Hands-on course. The teaching style is excellent. If you are looking for a DSA course and a beginner then your search end here. Just go for it guys. Many thanks to the instructor for creating this course5 STARS - This is the best computer science course I've taken. If you need to learn C++ and pass your technical interviews, this is the course to take. The explanations in the videos are extremely thorough, and I have reached out to the instructor several times on various questions, and he's always quick to respond and very helpful. In my experience, every MOOC that said its instructors would actively help you with problems lied, EXCEPT FOR THIS COURSE. TAKE THIS COURSE!5 STARS - This is the BEST COURSE on C++ Data Structures & Algorithms. The Instructors are the BEST. They Draw Everything out and Then EXPLAIN THE CONCEPTS VERY WELL & then CODE it. Also I Love Doing the LEETCODE ProblemSets. Absolutely Fantastic. Above my Expectations. I am taking this course for COMPETITIVE PROGRAMMING. It is the BEST COURSE. Thank you very much Ankit and Harsh. You guys are the BEST!Course HighlightsQuality Problems with hands-on codeIntuitive & Detailed ExplanationsHD VideosDeep focus on Problem SolvingBroaden your mindsetSTL Powerful features250+ HD Lectures200+ quality Problems60+ hours of interactive contentCode Evaluation ExercisesDoubt Solving within 6 hoursPractice ExercisesReal Time FeedbackLifetime AccessIndustry vetted curriculumCompletion CertificateOverview of TopicsArrays, Strings, Vectors, Binary SearchStacks, Queues, Linked ListsBinary Trees, BSTs, HeapsHashing, Pattern Matching, TriesBrute force, RecursionSliding Window, Two PointerSorting & Searching, GreedyGraphs Algorithms, Dynamic ProgrammingSo you want to learn and master Data Structure and Algorithm , I have done it. I have cracked interviews of top product based companies and landed job offers from many companies (Amazon, Samsung , Microsoft, Flipkart ...)This course is totally designed, with interative lectures, good quality problems, and is deeply focussed on problem solving. If you want to learn breath & depth of topics, this course is for you.So i have created this course keeping in mind university syllabus and also to make you ready to get those valuable internships and placements.You will top your university exams and will become interview ready at the same time.I know how professors teach in colleges , they just discuss theory , but hey I am not a professor instead a bro. I will teach you things which really matter . Also i have shared many tips and tricks in the course .So what are you waiting for ?? Master Data Structure and Algorithms , top you university exam and get those valuable internships and placements Still have doubt , see the course content , no one is teaching you variation of binary search , every other instructor will teach you standard binary search. I am also teaching Dynamic Programming which is difficult to teach and other instructors are not teaching this but its a very important topic and you must know it. We are solving 30+ problems on Recursion ,Note : This course is 100% practicalMy approach is very simple : discuss the relevant theory and then solve lots of problems . I teach concepts by solving lots of problems and you should be ready to solve lots of problems as Assignments , Quizzes etcEvery Data Structure is discussed, analysed and implemented with a Practical line-by-line coding.Source code for all Programs is available for you to downloadWith this complete course, you will become an expert in the core fundamentals of programming, Data Structures, Algorithms and its functioning with one of the most popular programming languages,C and C++. The involvement of the practical technique of problem-solving will give learners a better understanding of the concepts of the course. Learn to design efficient algorithms and become ready for future best jobs in the industry.As if this was not enough , I have shared tips and tricks on how to become good in competitive programming ( yes i have did CP in college) Source code for all Programs is available for you to download Sign up today!
Who this course is for
Undergraduate who want to Learn Data Structures Perfectly
Developer who want to get Deepest knowledge of Data Structure
Anyone interested in improving their problem solving skills
Anyone preparing for programming interviews
Homepage
Код:
https://www.udemy.com/course/data-structures-algorithms-using-c-zero-to-mastery/




Код:
Rapidgator
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No Password - Links are Interchangeable
 
Data Structures Demystified - Unlocking the Algorithmic Mind

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Free Download Data Structures Demystified - Unlocking the Algorithmic Mind
Published 11/2024
Created by Giri Venkataramanan
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 24 Lectures ( 1h 8m ) | Size: 286 MB

Building Efficient Solutions Through Practical Coding and Problem-Solving
What you'll learn
Master key data structures and algorithms for efficient coding.
Optimize problem-solving and analytical skills for complex challenges.
Apply concepts in real-world software solutions.
Prepare for technical interviews with hands-on coding practice.
Requirements
Basic knowledge of programming in any language
Description
Data Structures Demystified: Unlocking the Algorithmic Mind" is designed to help you build a solid foundation in data structures and algorithms, equipping you with the skills needed to solve complex problems and optimize your code for maximum efficiency. In this course, you'll explore fundamental concepts such as arrays, linked lists, stacks, queues, trees, graphs, sorting, searching algorithms, and more, with a strong focus on practical application.Through hands-on coding exercises and real-world examples, you'll learn how to analyze the performance of different algorithms, select the right data structures for various scenarios, and approach problems with a systematic, algorithmic mindset. This course is ideal for aspiring software developers, computer science students, and professionals preparing for technical interviews who want to gain a competitive edge.No matter your background, whether you're just starting out or looking to refresh your knowledge, this course provides step-by-step guidance to deepen your understanding and enhance your problem-solving capabilities. By the end of the course, you'll be able to craft efficient solutions, optimize code performance, and confidently tackle algorithmic challenges in both technical interviews and real-world projects. Join us and unlock the power of data structures and algorithms!Start your journey into the Data World to unleash the potential!!
Who this course is for
This course is ideal for aspiring software developers, computer science students, coding enthusiasts, and professionals preparing for technical interviews. It's also great for anyone looking to strengthen their problem-solving skills and deepen their understanding of data structures and algorithms.
Homepage
Код:
https://www.udemy.com/course/data-structures-demystified-unlocking-the-algorithmic-mind/




Код:
Rapidgator
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Data Structures in JavaScript BSTs, Queues, and Stacks

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Free Download Data Structures in JavaScript BSTs, Queues, and Stacks
Released: 11/2024
Duration: 52m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 107 MB
Level: Beginner | Genre: eLearning | Language: English
As a developer, you need to be able to leverage a wide variety of data structures if you want to write more efficient code in JavaScript. In this interactive coding course, instructor Tiffany Graves shows you how to use three of the most common JavaScript data structures-binary search trees (BSTs), queues, and stacks. Explore the best practices for using each of the three different data structures to store data with built-in functions that vary in time and space complexity. This course includes Code Challenges powered by CoderPad, so you can get feedback in real time and practice applying your new skills.

Homepage
Код:
https://www.linkedin.com/learning/data-structures-in-javascript-bsts-queues-and-stacks



Код:
Rapidgator
https://rg.to/file/82e93691b309105148d9c1fa11606390/tiqvz.Data.Structures.in.JavaScript.BSTs.Queues.and.Stacks.rar.html
Fikper Free Download
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Data Visualization & Storytelling - The Best All-in-One Guide

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Free Download Data Visualization & Storytelling - The Best All-in-One Guide
Published 11/2024
Created by Udicine™ Society
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 20 Lectures ( 2h 28m ) | Size: 1.21 GB

Learn to create impactful data visualizations and compelling stories with interactive charts in Excel.
What you'll learn
Understand the fundamentals of data visualization (Learn the importance of presenting data clearly and effectively to communicate insights.)
Learn best practices for data presentation (Explore techniques for simplifying complex data and making your charts accessible to a wide audience.)
Master essential chart types (column chart, bar chart, line chart, pie chart, waterfall chart, histogram, and combo charts, and more.)
Create dynamic and customizable data visualization( with Excel interactive features: dropdown lists, radio buttons, checkboxes, spin buttons, scroll bars.)
Understand the role of storytelling in data (Learn how to use storytelling techniques to make data-driven insights more compelling and understandable.)
Utilize storytelling to enhance data interpretation (Implement storytelling strategies to make data insights compelling and accessible for diverse audiences.)
Requirements
Basic Excel Knowledge: Familiarity with Microsoft Excel, including basic data entry, formatting, and using simple formulas (e.g., SUM, AVERAGE).
Access to Microsoft Excel: Learners should have access to Microsoft Excel 2016 or later, as the course will use its features for creating interactive charts and dashboards.
Curiosity about Data: A genuine interest in working with data, whether for business, personal projects, or academic purposes, will help learners get the most out of the course.
No Prior Data Visualization Experience Required: This course is designed to accommodate all skill levels, including beginners. Advanced skills are not necessary, as each concept will be explained step-by-step.
Description
Welcome to Data Visualization & Storytelling: The Best All-in-One Guide! This course is specifically designed to help individuals unlock the power of data by mastering Excel's charting and storytelling capabilities, transforming raw data into actionable insights.Why Do I Need to Learn Data Visualization & Storytelling?Data visualization is a crucial skill in today's data-driven world. It enables professionals to communicate complex information in a clear, engaging, and impactful way. This course will equip you with the tools and techniques needed to turn raw data into meaningful stories.Effective Data Presentation: Learn how to create visually compelling charts such as column, bar, pie, line, waterfall, histogram, and combo charts. These visual tools help break down complex data for better understanding.Interactive Data Exploration: Learn how to add interactivity to your charts using Excel's features such as dropdown lists, radio buttons, checkboxes, spin buttons, and scroll bars, making your visualizations dynamic and user-friendly.Tell Data-Driven Stories: Master the art of data storytelling by crafting narratives that highlight key insights, making data more memorable and actionable for your audience.Improved Decision Making: By learning to visualize data effectively, you'll be able to support data-driven decisions in your personal or professional life, leading to better outcomes.Why Should I Enroll in This Course?Whether you're a beginner or already working with data, this course offers a practical, hands-on approach to mastering data visualization and storytelling. You'll gain skills that are in high demand across industries, including business, marketing, research, and more.No Experience Required: Whether you're new to Excel or an experienced user, this course is designed for all skill levels. We'll guide you through each concept step-by-step.Create Interactive and Dynamic Visuals: Learn how to build interactive charts in Excel, adding value to your data presentations by allowing users to explore different scenarios with ease.Master Data Storytelling: Transform raw data into compelling stories that drive decision-making and captivate your audience. This is a highly sought-after skill that enhances your professional and personal projects.Career-Boosting Skills: Data visualization is a highly valuable skill that can elevate your career. The ability to convey data insights clearly is a key asset for professionals in virtually every field.Real-World Applications: By the end of the course, you'll have the expertise to create polished, interactive, and insightful data visualizations for business, personal, or academic use.30-Day Money-Back Guarantee!Your investment is risk-free with our 30-day money-back guarantee. If, for any reason, you're not satisfied with the course content or delivery, you can request a full refund within the first 30 days. We're confident that this course will empower you with the skills to transform data into powerful visual stories.Whether you're looking to enhance your career, make data-driven decisions, or simply gain new skills, this course is tailored to meet your needs.=> Enroll Now, and see you in the course!Udicine™ Society
Who this course is for
Beginners and Aspiring Data Analysts: If you're new to data analysis or want to develop a strong foundation in data visualization, this course will guide you through essential techniques and tools.
Professionals Looking to Enhance Their Data Skills: Business professionals, marketers, project managers, and anyone who works with data regularly will benefit from learning how to create effective charts, graphs, and interactive dashboards in Excel.
Educators and Researchers: Teachers, trainers, and researchers who need to present data in a compelling way will gain techniques to make complex information accessible and engaging.
Small Business Owners and Entrepreneurs: Individuals who run their own businesses can leverage data visualization to better understand their performance metrics and make informed decisions.
Students and Career Switchers: College students or those looking to pivot into a data-focused role can build valuable skills in data storytelling and visualization, which are highly in demand across industries.
Anyone Curious About Data Storytelling: If you have an interest in using data to tell stories and make better decisions, this course offers a step-by-step approach to build skills, even if you're starting with no prior experience.
Homepage
Код:
https://www.udemy.com/course/data-visualization-storytelling-the-best-all-in-one-guide/




Код:
Rapidgator
https://rg.to/file/0f02efc8a5626774c5f6f62626eb23ef/elklt.Data.Visualization..Storytelling.The.Best.AllinOne.Guide.part1.rar.html
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Data to Defense - A Guide to Cybersecurity Analytics

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Free Download Data to Defense - A Guide to Cybersecurity Analytics
Published 11/2024
Created by John Boyle
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 25 Lectures ( 2h 24m ) | Size: 759 MB

Mastering Cybersecurity Analytics: From Fundamentals to Advanced Techniques
What you'll learn
Understand the fundamental concepts of cybersecurity analytics and its role in protecting digital assets.
Acquire knowledge of various data sources used in cybersecurity analytics, including network traffic, log files, and sensor data.
Learn data preprocessing techniques to prepare data for analysis, such as cleaning, normalization, and feature engineering.
Explore machine learning algorithms relevant to cybersecurity analytics, including anomaly detection, classification, and regression.
Develop skills in data visualization to effectively communicate cybersecurity insights.
Understand the ethical implications of cybersecurity analytics and the importance of privacy and compliance.
Gain practical experience through hands-on projects and case studies.
Requirements
Basic understanding of computer science
Basic understanding of programming (e.g., Python)
Basic understanding of statistics
Description
This comprehensive course is designed to equip you with the essential skills and knowledge to excel in the field of cybersecurity analytics. Whether you're a cybersecurity professional, data analyst, or aspiring security analyst, this course will provide you with a solid foundation and advanced techniques to effectively analyze security data and protect your organization's assets.What You'll Learn:You will learn the fundamental concepts of cybersecurity analytics, including data-driven security and its importance. You will explore various data sources, such as network traffic, logs, and threat intelligence feeds, and master techniques for data cleaning, transformation, and enrichment.You will also delve into data analysis and visualization, applying statistical analysis techniques and utilizing powerful visualization tools like Matplotlib and Seaborn to uncover insights from data.The course covers a wide range of machine learning techniques, including supervised and unsupervised learning algorithms. You will learn how to build and evaluate machine learning models for tasks like anomaly detection, intrusion detection, and threat classification. Additionally, you will explore advanced techniques like deep learning for complex security challenges.You will gain a deep understanding of threat intelligence and hunting, including identifying indicators of compromise (IOCs) and conducting threat hunting. You will also learn how to effectively use Security Information and Event Management (SIEM) systems to analyze security events and detect threats.Finally, you will explore the power of automation and orchestration in cybersecurity. You will learn how to automate routine tasks, streamline incident response, and improve overall security efficiency.What You'll Learn:Fundamental Concepts:Understand the core concepts of cybersecurity analytics, including data-driven security and its importance.Learn about the role of cybersecurity analysts and the key skills required.Data Acquisition and Preparation:Explore various sources of cybersecurity data, such as network traffic, logs, and threat intelligence feeds.Master techniques for data cleaning, transformation, and enrichment.Learn how to handle missing data, outliers, and inconsistencies.Data Analysis and Visualization:Apply statistical analysis techniques to uncover insights from data.Utilize powerful visualization tools to present data effectively.Gain hands-on experience with data visualization libraries like Matplotlib and Seaborn.Machine Learning for Cybersecurity:Dive into machine learning concepts and algorithms relevant to cybersecurity.Learn how to build and evaluate machine learning models for tasks like anomaly detection, intrusion detection, and threat classification.Explore advanced techniques like deep learning for complex security challenges.Threat Intelligence and Hunting:Understand the role of threat intelligence in proactive security.Learn how to identify indicators of compromise (IOCs) and conduct threat hunting.Explore techniques for analyzing threat actor tactics, techniques, and procedures (TTPs).SIEM and Security Automation:Master the concepts of Security Information and Event Management (SIEM).Learn how to integrate SIEM with other security tools to enhance threat detection and response.Explore automation tools and frameworks for streamlining security operations.Understand the benefits of orchestration for incident response.
Who this course is for
Cybersecurity Professionals: Security analysts, incident responders, threat intelligence analysts, and security operations center (SOC) analysts.
Data Scientists and Analysts: Data scientists and analysts interested in applying their skills to cybersecurity.
IT Professionals: Network engineers, system administrators, and IT operations professionals who want to enhance their security skills.
Students and Academics: Computer science, information technology, and cybersecurity students.
Cybersecurity Enthusiasts: Individuals with a passion for cybersecurity and a desire to learn more.
Homepage
Код:
https://www.udemy.com/course/cybersecurity-analytics/




Код:
Rapidgator
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Deceased Estates How To Draft An L&D Account

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Free Download Deceased Estates How To Draft An L&D Account
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.70 GB | Duration: 3h 1m
Understand the law and how transactions is to be treated in the L&D Account

What you'll learn
Surviving spouse's inheritance
Administration costs
Transfer duty
A dependent claims that they have not been properly provided for under the Will
Sale of property or personal assets
Someone refuses to turn over an asset belonging to the estate - costs involved
Deceased had other children nobody knew about - how to adjust L&D Account
Personal loan accounts owed to companies/ business from deceased borrowed from business then payable back on death
Outstanding tax returns and TAX owed
Requirements
No prerequistes required
Description
Understanding the legal aspects and considerations of Deceased Estates is one thing but drafting the actual L&D Account is quite another.Of course, it is important to understand the law and how certain specific transactions is to be treated in the L&D Account, however, completing an L&D Account from start to finish, without hesitation and uncertainty, is what every Executor aims for. Knowing that every single aspect of that account has been carefully considered and correctly recorded is part of the successful winding up of a deceased estate in the shortest period of time.Join us for this very insightful course, during which the following transactions will be demonstrated on the L&D Account as a base for the demonstration.Topics Discussed:Surviving spouse's inheritance (section 4q)Section 4APolicies paid directly to third partiesAdministration costsOther exemptionsTransfer dutyAny SARS tax is an administration cost in the estateA dependent claims that they have not been properly provided for under the WillSale of property or personal assetsCreditorsSomeone refuses to turn over an asset belonging to the estate - costs involvedJoint ownership of assetsDeceased had other children nobody knew about - how to adjust L&D AccountUnder estimation of Estate DutyPersonal loan accounts owed to companies/ business from deceased borrowed from business then payable back on deathCash shortfallPossible capital gains taxOutstanding tax returns and TAX owedDivorce ordersThis is a practical and interactive live demonstration.The presenter is going to demonstrate how the above elements are to be recorded in the L&D Account and how estate duty will be applied.
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Deceased Estates: How to Draft an L&D Account
Lecture 2 Part 1
Lecture 3 Part 2
Lecture 4 Part 3
Lecture 5 Part 4
Lecture 6 Part 5
Lecture 7 Part 6
Estate Administrators,Estate Agents,Business Professionals,Business Owners
Homepage
Код:
https://www.udemy.com/course/deceased-estates-how-to-draft-an-ld-account/


Код:
Rapidgator
https://rg.to/file/aad2efaa117d3184fef83495bb8edfb5/hvreu.Deceased.Estates.How.To.Draft.An.LD.Account.part2.rar.html
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Decision Making For Leaders by Peter Alkema

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Free Download Decision Making For Leaders by Peter Alkema
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.98 GB | Duration: 5h 19m
Master Leadership Decision-Making:From Ethical Choices to Crisis Management,Strategic Planning & Data Analysis Technique

What you'll learn
Analyze various decision-making processes to determine the most effective strategy for leadership situations.
Interpret and use data effectively to make informed leadership decisions.
Apply emotional intelligence principles to improve decision-making outcomes and team dynamics.
Identify and adapt your personal decision-making style to lead more effectively.
Evaluate real-life leadership decisions to understand the impact of different approaches.
Develop critical thinking skills to analyze problems and make logical leadership decisions.
Use logical reasoning techniques to improve decision-making accuracy and effectiveness.
Utilize critical thinking tools to enhance decision-making processes in leadership roles.
Assess case studies to identify critical thinking applications in leadership decision-making.
Interpret data accurately to support informed decision-making in a business context.
Apply data visualization techniques to present data effectively for leadership decision-making.
Utilize business intelligence tools to gather insights and inform leadership decisions.
Predict outcomes using predictive analytics to make informed leadership decisions.
Identify risks in leadership scenarios and evaluate their potential impact.
Develop risk mitigation strategies to minimize potential negative outcomes in leadership decisions.
Make informed decisions under uncertainty by assessing possible outcomes and their implications.
Create a strategic plan that aligns with organizational goals and objectives.
Implement and adjust strategic plans based on ongoing evaluations and feedback.
Improve decision quality by applying metrics and evaluation techniques in leadership scenarios.
Utilize ethical frameworks to navigate dilemmas and make values-based leadership decisions.
Requirements
There are no requirements or pre-requisites for this course, but the items listed below are a guide to useful background knowledge which will increase the value and benefits of this course.
Basic understanding of leadership principles and practices.
Familiarity with basic data analysis and interpretation.
An interest in improving decision-making skills and critical thinking.
Description
Are you ready to elevate your leadership skills and make impactful decisions with confidence and precision? Welcome to our comprehensive course on Decision Making in Leadership, where you will delve into the intricacies of effective decision-making processes and strategies to become a visionary leader in your organization.At[Course Name], we are passionate about empowering individuals like you to navigate complex decision environments, harness data-driven insights, and lead with integrity and innovation. Our team of experienced professionals has curated this course to equip you with the critical thinking skills, strategic planning techniques, and ethical decision-making frameworks necessary to thrive in today's dynamic business landscape.Throughout this course, you will embark on a transformative journey, starting with understanding the fundamentals of decision-making and exploring the role of emotional intelligence in leadership. You will analyze real-life examples, engage in critical thinking exercises, and master data analysis tools to make informed decisions that drive organizational success.As you progress, you will delve into risk assessment and management strategies, strategic planning methodologies, and the nuances of decision quality in leadership. You will discover how to navigate ethical dilemmas, adapt to complex decision environments, and make sound decisions under pressure, all while mitigating psychological biases that may impact your judgment.Moreover, our course will explore the integration of technology in decision-making processes, crisis management strategies, and the importance of continual improvement to enhance your decision-making capabilities. You will have the opportunity to engage in hands-on simulations, case studies, and reflective practices to solidify your learning and apply your newfound knowledge in real-world scenarios.By the end of this course, you will emerge as a strategic leader with the ability to align decisions with organizational goals, drive innovation, and promote sustainability through conscious decision-making practices. Whether you are a seasoned professional seeking to enhance your leadership skills or a budding entrepreneur looking to sharpen your decision-making acumen, our course offers unparalleled value and insights tailored to your journey.Join us on this transformative learning experience and unlock your potential to make impactful decisions that shape the future of your organization. Enroll in our Decision Making in Leadership course today and embark on a path towards becoming a resilient and visionary leader in today's ever-evolving business landscape. Let's embark on this exciting journey together.
Overview
Section 1: Fundamentals of Decision Making in Leadership
Lecture 1 Understanding Decision-Making Process
Lecture 2 Download The *Amazing* +100 Page Workbook For this Course
Lecture 3 Student Self Intro
Lecture 4 Importance of Data in Decision Making
Lecture 5 Role of Emotional Intelligence
Lecture 6 Decision-Making Styles in Leadership
Lecture 7 Real-Life Decision-Making Examples
Lecture 8 Let's Celebrate Your Progress In This Course: 25% > 50% > 75% > 100%!!
Section 2: Critical Thinking for Leaders
Lecture 9 Developing Critical Thinking Skills
Lecture 10 Analyzing Information Effectively
Lecture 11 Logical Reasoning in Decision Making
Lecture 12 Critical Thinking Tools for Leaders
Lecture 13 Case Studies on Critical Thinking in Leadership
Section 3: Data Analysis for Informed Decisions
Lecture 14 Data Interpretation Skills
Lecture 15 Data Visualization Techniques
Lecture 16 Business Intelligence Tools
Lecture 17 Predictive Analytics in Decision Making
Lecture 18 Real-Life Data Analysis Scenarios
Section 4: Risk Assessment and Management Strategies
Lecture 19 Risk Identification in Leadership
Lecture 20 Risk Analysis and Evaluation
Lecture 21 Risk Mitigation Approaches
Lecture 22 Decision-making under Uncertainty
Lecture 23 Case Studies on Risk Management in Leadership
Section 5: Strategic Planning for Effective Decision Making
Lecture 24 Components of Strategic Planning
Lecture 25 Aligning Decisions with Strategic Goals
Lecture 26 Implementation Planning
Lecture 27 Monitoring and Adjusting Strategies
Lecture 28 Real-Life Examples of Strategic Decision Making
Lecture 29 Student Self Intro
Lecture 30 You've Achieved 25% >> Let's Celebrate Your Progress And Keep Going To 50% >>
Section 6: Decision Quality in Leadership
Lecture 31 Defining Decision Quality
Lecture 32 Improving Decision-Making Quality
Lecture 33 Balancing Speed and Quality
Lecture 34 Decision Quality Metrics
Lecture 35 Case Studies on Decision Quality in Leadership
Section 7: Ethical Decision Making
Lecture 36 Ethical Frameworks in Leadership
Lecture 37 Ethical Dilemmas in Decision Making
Lecture 38 Values-Based Decision Making
Lecture 39 Ethical Leadership Practices
Lecture 40 Real-Life Scenarios of Ethical Decision Making
Section 8: Complex Decision Environments
Lecture 41 Understanding Complex Decision Variables
Lecture 42 Navigating Uncertainty
Lecture 43 Systems Thinking in Decision Making
Lecture 44 Adaptive Decision Making Strategies
Lecture 45 Case Studies on Decisions in Complex Environments
Section 9: Decision Making Under Pressure
Lecture 46 Handling High-Stress Decision Scenarios
Lecture 47 Maintaining Clarity and Focus
Lecture 48 Strategies for Quick Decisions
Lecture 49 Crisis Management Decision Making
Lecture 50 Real-Life Examples of Decisions Under Pressure
Section 10: Psychological Biases in Decision Making
Lecture 51 Cognitive Biases Impacting Decisions
Lecture 52 Awareness and Mitigation of Biases
Lecture 53 Overcoming Decision-Making Blind Spots
Lecture 54 Rational Decision-Making Techniques
Lecture 55 Case Studies on Psychological Biases
Lecture 56 You've Achieved 50% >> Let's Celebrate Your Progress And Keep Going To 75% >>
Section 11: Test your knowledge now to achieve your goals!
Section 12: Decision Making Models for Leaders
Lecture 57 Decision-Making Frameworks Overview
Lecture 58 Rational Decision Model
Lecture 59 Intuitive Decision-Making
Lecture 60 Collaborative Decision Models
Lecture 61 Adaptive Decision-Making Models
Section 13: Decision Making in Organizational Change
Lecture 62 Leading Change through Decision Making
Lecture 63 Change Management Decision Points
Lecture 64 Decision Communication in Change
Lecture 65 Anticipating Change Impacts
Lecture 66 Case Studies on Decision Making in Change
Section 14: Innovation and Decision Making
Lecture 67 Fostering Innovation through Decisions
Lecture 68 Decision Processes for Innovation
Lecture 69 Risk-Taking for Innovation
Lecture 70 Decision Criteria for Innovative Projects
Lecture 71 Real-Life Examples of Innovation Decisions
Section 15: Global Perspectives on Decision Making
Lecture 72 Cultural Influence on Decisions
Lecture 73 Global Market Analysis for Decisions
Lecture 74 Cross-Border Decision Challenges
Lecture 75 Decision-making in Diverse Teams
Lecture 76 International Business Decision Cases
Section 16: Strategic Decision Alignment
Lecture 77 Strategic Decision Alignment Framework
Lecture 78 Ensuring Consistency in Decision Making
Lecture 79 Decision-Making Hierarchy
Lecture 80 Aligning Decision with Organizational Objectives
Lecture 81 Effective Strategic Decision Implementation
Lecture 82 You've Achieved 75% >> Let's Celebrate Your Progress And Keep Going To 100% >>
Section 17: Decision Making for Sustainable Practices
Lecture 83 Sustainability Decision Framework
Lecture 84 Ethical Considerations in Sustainable Decisions
Lecture 85 Balancing Profit and Sustainable Choices
Lecture 86 Evaluating Environmental Impact
Lecture 87 Case Studies on Sustainable Decision Making
Section 18: Technology Integration in Decision Making
Lecture 88 AI and Machine Learning for Decisions
Lecture 89 Data Analytics Tools for Decision Making
Lecture 90 Tech-Driven Decision Support Systems
Lecture 91 Impact of Technology on Decision Quality
Lecture 92 Tech Integration Case Studies in Decision Making
Section 19: Crisis Decision Management
Lecture 93 Crisis Decision Preparedness
Lecture 94 Swift Crisis Response Decisions
Lecture 95 Decision Making in High-Stress Situations
Lecture 96 Post-Crisis Decision Evaluation
Lecture 97 Real-Time Crisis Decision Examples
Section 20: Continual Improvement in Decision Making
Lecture 98 Feedback Mechanisms for Decisions
Lecture 99 Decision Review and Learn Cycle
Lecture 100 Iterative Decision Making Process
Lecture 101 Strategies for Decision Improvement
Lecture 102 Continuous Improvement Case Studies
Section 21: Strategic Leadership Decision Simulation
Lecture 103 Leadership Decision Simulation Exercises
Lecture 104 Strategic Scenario Analysis
Lecture 105 Virtual Leadership Decision Challenges
Lecture 106 Strategic Decision-Making Competitions
Lecture 107 Final Reflective Practice on Leadership Decisions
Lecture 108 You've Achieved 100% >> Let's Celebrate! Remember To Share Your Certificate!!
Section 22: Test your knowledge now to achieve your goals!
Section 23: Your Assignment: Write down goals to improve your life and achieve your goals!!
Emerging Leaders and Managers looking to sharpen their decision-making skills.,Business Executives interested in enhancing strategic planning and risk management capabilities.,Project Managers aiming to improve project outcomes through better decision-making processes.,HR Professionals seeking to implement ethical decision-making frameworks within their organizations.,Data Analysts and Scientists looking to apply their skills more effectively in predictive analytics and informed decision-making.,Sustainability Officers aiming to integrate sustainable practices into organizational decision-making.
Homepage
Код:
https://www.udemy.com/course/decision-making-for-leaders-x/


Код:
Rapidgator
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Deep Learning Bootcamp - Neural Networks With Python, Pytorch

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Free Download Deep Learning Bootcamp - Neural Networks With Python, Pytorch
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 6.00 GB | Duration: 14h 21m
Master Neural Networks, DNNs, and CNNs with Python, PyTorch, and TensorFlow in this all-in-one Deep Learning Bootcamp.

What you'll learn
• The basics of Machine Learning.
• The basics of Neural Networks.
• The basics of training a Deep Neural Network (DNN) using Gradient Descent Algorithm.
• Using Deep Learning for IRIS dataset.
• A solid understanding of tensors and their operations in PyTorch.
• The ability to build and train basic to complex neural networks.
• Knowledge of different loss functions, optimizers, and activation functions.
• A completed project on brain tumor detection from MRI images, showcasing your skills in deep learning and PyTorch.
• A Solid Grasp of TensorFlow Basics
• Hands-on Experience in Building Deep Learning Models
• Knowledge of Model Training, Evaluation, and Optimization
• Confidence to Explore More Complex AI and Machine Learning Projects
Requirements
• No prior knowledge of Deep Learning or Math is needed. You will start from the basics and build your knowledge of the subject step by step.
• Basic understanding of Python programming.
No prior experience with TensorFlow is required, but a basic understanding of machine learning concepts and Python will be helpful.
Description
Are you ready to unlock the full potential of Deep Learning and AI by mastering not just one but multiple tools and frameworks? This comprehensive course will guide you through the essentials of Deep Learning using Python, PyTorch, and TensorFlow-the most powerful libraries and frameworks for building intelligent models.Whether you're a beginner or an experienced developer, this course offers a step-by-step learning experience that combines theoretical concepts with practical hands-on coding. By the end of this journey, you'll have developed a deep understanding of neural networks, gained proficiency in applying Deep Neural Networks (DNNs) to solve real-world problems, and built expertise in cutting-edge deep learning applications like Convolutional Neural Networks (CNNs) and brain tumor detection from MRI images.Why Choose This Course?This course stands out by offering a comprehensive learning path that merges essential aspects from three leading frameworks: Python, PyTorch, and TensorFlow. With a strong emphasis on hands-on practice and real-world applications, you'll quickly advance from fundamental concepts to mastering deep learning techniques, culminating in the creation of sophisticated AI models.Key Highlights:Python: Learn Python from the basics, progressing to advanced-level programming essential for implementing deep learning algorithms.PyTorch: Master PyTorch for neural networks, including tensor operations, optimization, autograd, and CNNs for image recognition tasks.TensorFlow: Unlock TensorFlow's potential for creating robust deep learning models, utilizing tools like Tensorboard for model visualization.Real-world Projects: Apply your knowledge to exciting projects like IRIS classification, brain tumor detection from MRI images, and more.Data Preprocessing & ML Concepts: Learn crucial data preprocessing techniques and key machine learning principles such as Gradient Descent, Back Propagation, and Model Optimization.Course Content Overview:Module 1: Introduction to Deep Learning and PythonIntroduction to the course structure, learning objectives, and key frameworks.Overview of Python programming: from basics to advanced, ensuring you can confidently implement any deep learning concept.Module 2: Deep Neural Networks (DNNs) with Python and NumPyProgramming with Python and NumPy: Understand arrays, data frames, and data preprocessing techniques.Building DNNs from scratch using NumPy.Implementing machine learning algorithms, including Gradient Descent, Logistic Regression, Feed Forward, and Back Propagation.Module 3: Deep Learning with PyTorchLearn about tensors and their importance in deep learning.Perform operations on tensors and understand autograd for automatic differentiation.Build basic and complex neural networks with PyTorch.Implement CNNs for advanced image recognition tasks.Final Project: Brain Tumor Detection using MRI Images.Module 4: Mastering TensorFlow for Deep LearningDive into TensorFlow and understand its core features.Build your first deep learning model using TensorFlow, starting with a simple neuron and progressing to Artificial Neural Networks (ANNs).TensorFlow Playground: Experiment with various models and visualize performance.Explore advanced deep learning projects, learning concepts like gradient descent, epochs, backpropagation, and model evaluation.Who Should Take This Course?Aspiring Data Scientists and Machine Learning Enthusiasts eager to develop deep expertise in neural networks.Software Developers looking to expand their skillset with PyTorch and TensorFlow.Business Analysts and AI Enthusiasts interested in applying deep learning to real-world problems.Anyone passionate about learning how deep learning can drive innovation across industries, from healthcare to autonomous driving.What You'll Learn:Programming with Python, NumPy, and Pandas for data manipulation and model development.How to build and train Deep Neural Networks and Convolutional Neural Networks using PyTorch and TensorFlow.Practical deep learning applications like brain tumor detection and IRIS classification.Key machine learning concepts, including Gradient Descent, Model Optimization, and more.How to preprocess and handle data efficiently using tools like DataLoader in PyTorch and Transforms for data augmentation.Hands-on Experience:By the end of this course, you will not only have learned the theory but will also have built multiple deep learning models, gaining hands-on experience in real-world projects.
Overview
Section 1: Deep Learning:Deep Neural Network for Beginners Using Python
Lecture 1 Promo & Highlights
Lecture 2 Introduction: Introduction to Instructor and Aisciences
Lecture 3 Links for the Course's Materials and Codes
Lecture 4 Basics of Deep Learning: Problem to Solve Part 1
Lecture 5 Basics of Deep Learning: Problem to Solve Part 2
Lecture 6 Basics of Deep Learning: Problem to Solve Part 3
Lecture 7 Basics of Deep Learning: Linear Equation
Lecture 8 Basics of Deep Learning: Linear Equation Vectorized
Lecture 9 Basics of Deep Learning: 3D Feature Space
Lecture 10 Basics of Deep Learning: N Dimensional Space
Lecture 11 Basics of Deep Learning: Theory of Perceptron
Lecture 12 Basics of Deep Learning: Implementing Basic Perceptron
Lecture 13 Basics of Deep Learning: Logical Gates for Perceptrons
Lecture 14 Basics of Deep Learning: Perceptron Training Part 1
Lecture 15 Basics of Deep Learning: Perceptron Training Part 2
Lecture 16 Basics of Deep Learning: Learning Rate
Lecture 17 Basics of Deep Learning: Perceptron Training Part 3
Lecture 18 Basics of Deep Learning: Perceptron Algorithm
Lecture 19 Basics of Deep Learning: Coading Perceptron Algo (Data Reading & Visualization)
Lecture 20 Basics of Deep Learning: Coading Perceptron Algo (Perceptron Step)
Lecture 21 Basics of Deep Learning: Coading Perceptron Algo (Training Perceptron)
Lecture 22 Basics of Deep Learning: Coading Perceptron Algo (Visualizing the Results)
Lecture 23 Basics of Deep Learning: Problem with Linear Solutions
Lecture 24 Basics of Deep Learning: Solution to Problem
Lecture 25 Basics of Deep Learning: Error Functions
Lecture 26 Basics of Deep Learning: Discrete vs Continuous Error Function
Lecture 27 Basics of Deep Learning: Sigmoid Function
Lecture 28 Basics of Deep Learning: Multi-Class Problem
Lecture 29 Basics of Deep Learning: Problem of Negative Scores
Lecture 30 Basics of Deep Learning: Need of Softmax
Lecture 31 Basics of Deep Learning: Coding Softmax
Lecture 32 Basics of Deep Learning: One Hot Encoding
Lecture 33 Basics of Deep Learning: Maximum Likelihood Part 1
Lecture 34 Basics of Deep Learning: Maximum Likelihood Part 2
Lecture 35 Basics of Deep Learning: Cross Entropy
Lecture 36 Basics of Deep Learning: Cross Entropy Formulation
Lecture 37 Basics of Deep Learning: Multi Class Cross Entropy
Lecture 38 Basics of Deep Learning: Cross Entropy Implementation
Lecture 39 Basics of Deep Learning: Sigmoid Function Implementation
Lecture 40 Basics of Deep Learning: Output Function Implementation
Lecture 41 Deep Learning: Introduction to Gradient Decent
Lecture 42 Deep Learning: Convex Functions
Lecture 43 Deep Learning: Use of Derivatives
Lecture 44 Deep Learning: How Gradient Decent Works
Lecture 45 Deep Learning: Gradient Step
Lecture 46 Deep Learning: Logistic Regression Algorithm
Lecture 47 Deep Learning: Data Visualization and Reading
Lecture 48 Deep Learning: Updating Weights in Python
Lecture 49 Deep Learning: Implementing Logistic Regression
Lecture 50 Deep Learning: Visualization and Results
Lecture 51 Deep Learning: Gradient Decent vs Perceptron
Lecture 52 Deep Learning: Linear to Non Linear Boundaries
Lecture 53 Deep Learning: Combining Probabilities
Lecture 54 Deep Learning: Weighted Sums
Lecture 55 Deep Learning: Neural Network Architecture
Lecture 56 Deep Learning: Layers and DEEP Networks
Lecture 57 Deep Learning: Multi Class Classification
Lecture 58 Deep Learning: Basics of Feed Forward
Lecture 59 Deep Learning: Feed Forward for DEEP Net
Lecture 60 Deep Learning: Deep Learning Algo Overview
Lecture 61 Deep Learning: Basics of Back Propagation
Lecture 62 Deep Learning: Updating Weights
Lecture 63 Deep Learning: Chain Rule for BackPropagation
Lecture 64 Deep Learning: Sigma Prime
Lecture 65 Deep Learning: Data Analysis NN Implementation
Lecture 66 Deep Learning: One Hot Encoding (NN Implementation)
Lecture 67 Deep Learning: Scaling the Data (NN Implementation)
Lecture 68 Deep Learning: Splitting the Data (NN Implementation)
Lecture 69 Deep Learning: Helper Functions (NN Implementation)
Lecture 70 Deep Learning: Training (NN Implementation)
Lecture 71 Deep Learning: Testing (NN Implementation)
Lecture 72 Optimizations: Underfitting vs Overfitting
Lecture 73 Optimizations: Early Stopping
Lecture 74 Optimizations: Quiz
Lecture 75 Optimizations: Solution & Regularization
Lecture 76 Optimizations: L1 & L2 Regularization
Lecture 77 Optimizations: Dropout
Lecture 78 Optimizations: Local Minima Problem
Lecture 79 Optimizations: Random Restart Solution
Lecture 80 Optimizations: Vanishing Gradient Problem
Lecture 81 Optimizations: Other Activation Functions
Lecture 82 Final Project: Final Project Part 1
Lecture 83 Final Project: Final Project Part 2
Lecture 84 Final Project: Final Project Part 3
Lecture 85 Final Project: Final Project Part 4
Lecture 86 Final Project: Final Project Part 5
Section 2: PyTorch Power: From Zero to Deep Learning Hero - PyTorch
Lecture 87 Links for the Course's Materials and Codes
Lecture 88 Introduction: Module Content
Lecture 89 Introduction: Benefits of Framework
Lecture 90 Introduction: Installations and Setups
Lecture 91 Tensor: Introduction to Tensor
Lecture 92 Tensor: List vs Array vs Tensor
Lecture 93 Tensor: Arithmetic Operations
Lecture 94 Tensor: Tensor Operations
Lecture 95 Tensor: Auto-Gradiants
Lecture 96 Tensor: Activity Solution
Lecture 97 Tensor: Detaching Gradients
Lecture 98 Tensor: Loading GPU
Lecture 99 NN with Tensor: Introduction to Module
Lecture 100 NN with Tensor: Basic NN part 1
Lecture 101 NN with Tensor: Basic NN part 2
Lecture 102 NN with Tensor: Loss Functions
Lecture 103 NN with Tensor: Activation Functions & Hidden Layers
Lecture 104 NN with Tensor: Optimizers
Lecture 105 NN with Tensor: Data Loader & Dataset
Lecture 106 NN with Tensor: Activity
Lecture 107 NN with Tensor: Activity Solution
Lecture 108 NN with Tensor: Formating the Output
Lecture 109 NN with Tensor: Graph for Loss
Lecture 110 CNN: Introduction to Module
Lecture 111 CNN: CNN vs NN
Lecture 112 CNN: Introduction to Convolution
Lecture 113 CNN: Convolution Animations
Lecture 114 CNN: Convolution using Pytorch
Lecture 115 CNN: Introduction to Pooling
Lecture 116 CNN: Pooling using Numpy
Lecture 117 CNN: Pooling in Pytorch
Lecture 118 CNN: Introduction to Project
Lecture 119 CNN: Project (Data Loading)
Lecture 120 CNN: Project (Transforms)
Lecture 121 CNN: Project (DataLoaders)
Lecture 122 CNN: Project (CNN Architect)
Lecture 123 CNN: Project (Forward Propagation)
Lecture 124 CNN: Project (Training CNN)
Lecture 125 CNN: Project (Analyzing Model Output)
Lecture 126 CNN: Project (Making Predictions)
Section 3: TensorFlow Fundamentals: From Basics to Brilliant AI Project
Lecture 127 Links for the Course's Materials and Codes
Lecture 128 Introduction to TensorFlow: Module Introduction
Lecture 129 Introduction to TensorFlow: TensorFlow Definition and Properties
Lecture 130 Introduction to TensorFlow: Tensor Types and Tesnor Board
Lecture 131 Introduction to TensorFlow: How to use TensorFlow
Lecture 132 Introduction to TensorFlow: Google Colab
Lecture 133 Introduction to TensorFlow: Exercise
Lecture 134 Introduction to TensorFlow: Exercise Solution
Lecture 135 Introduction to TensorFlow: Quiz
Lecture 136 Introduction to TensorFlow: Quiz Solution
Lecture 137 Building your first deep learning Project: Module Introduction
Lecture 138 Building your first deep learning Project: ANNs
Lecture 139 Building your first deep learning Project: TensorFlow Playground
Lecture 140 Building your first deep learning Project: Load TF and Data
Lecture 141 Building your first deep learning Project: Model Training and Evaluation
Lecture 142 Building your first deep learning Project: Project
Lecture 143 Building your first deep learning Project: Project Implementation
Lecture 144 Building your first deep learning Project: Quiz
Lecture 145 Building your first deep learning Project: Quiz Solution
Lecture 146 Multi-layer Deep Learning Project: Module Introduction
Lecture 147 Multi-layer Deep Learning Project: Training and Epochs
Lecture 148 Multi-layer Deep Learning Project: Gradient Decent and Back Propagation
Lecture 149 Multi-layer Deep Learning Project: Bias Variance Trade-Off
Lecture 150 Multi-layer Deep Learning Project: Performance Metrics
Lecture 151 Multi-layer Deep Learning Project: Project-Sales Predition
Lecture 152 Multi-layer Deep Learning Project: Quiz
Lecture 153 Multi-layer Deep Learning Project: Quiz Solution
• Anyone interested in Data Science.,• People who want to master DNNs with real datasets in Deep Learning.,• People who want to implement DNNs in realistic projects.,• Software developers and data scientists looking to expand their skillset with PyTorch.,• Beginners who want to enter the field of deep learning and artificial intelligence.,• Anyone Curious About Deep Learning and TensorFlow
Homepage
Код:
https://www.udemy.com/course/deep-learning-bootcamp-neural-networks-with-python-pytorch/


Код:
Rapidgator
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Demystifying Agentic AI with ChatGPT Elevate Your Skills and Unlock New Potential

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Free Download Demystifying Agentic AI with ChatGPT Elevate Your Skills and Unlock New Potential
Released 11/2024
With Jules White
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 1h 18m 29s | Size: 192 MB

This course simplifies the concept of agentic AI, helping you understand how to interact with and harness these intelligent agents effectively.
Course details
Explore the power of agentic AI in this course with instructor Jules White. Jules simplifies the concept of agentic AI, helping you understand how to interact with and harness these intelligent agents effectively. Imagine agents autonomously scheduling meetings, drafting tailored reports, or even managing customer inquiries-all while you focus on strategic tasks. Learn how these agents work and gain the fundamental knowledge to start building AI in a new way, revolutionizing your approach to productivity and innovation.
Homepage
Код:
https://www.linkedin.com/learning/demystifying-agentic-ai-with-chatgpt-elevate-your-skills-and-unlock-new-potential




Код:
Rapidgator
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Deploy LLM App with Ollama and Langchain in Production

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Free Download Deploy LLM App with Ollama and Langchain in Production
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 7.16 GB | Duration: 12h 0m
Build AI chatbots, automate workflows, deploy on AWS. Master Langchain, Ollama, prompt engineering and RAG

What you'll learn
Set up and Integrate Ollama with Langchain: Students will learn how to install, configure, and operate Ollama alongside Langchain.
Build Custom Chatbots: Learners will develop skills to create chat applications with memory, history, advanced chatbot features using Streamlit and Langchain.
Use Prompt Templates, Chains, and Output Parsers: Students will master prompt templates and chaining methods (Sequential, Parallel, and Router Chains).
Deploy Real-World Applications: The course will guide students through deploying applications on AWS EC2
Requirements
Basic Python programming knowledge
Familiarity with APIs and web requests
Basic understanding of machine learning concepts
Access to a computer with internet for installations and setups
Description
This course is a practical guide to integrating Langchain and Ollama to build, automate, and deploy AI applications. Learn to set up these tools, create prompt templates, automate workflows, manage data retrieval, and deploy real-world applications on AWS. Each section is designed to provide you with hands-on skills and experience.What You Will LearnOllama & Langchain SetupComplete setup and installation of Ollama and Langchain.Configure base URLs and handle direct API calls.Establish the environment for efficient integration.Prompt EngineeringUnderstand AI, human, and system message prompts.Use AIPromptTemplate, Human, System, and ChatMessagePromptTemplate to shape responses.Explore the invoke method to control the model's behavior.Chains for Workflow AutomationLearn Sequential, Parallel, and Router Chains to build flexible workflows.Work with custom chains and explore Chain Runnables for added automation.Implement real-world workflows using Langchain's chaining capabilities.Output ParsingFormat data with parsers like JSON, CSV, Markdown, and Pydantic.Parse structured output and use date-time output handling for organized data.Chat Message MemoryUse BaseChatMessageHistory and InMemoryChatMessageHistory for managing chat sessions.Create chat applications with memory to improve user experience.Build and Deploy ChatbotsBuild a chatbot application using Streamlit.Maintain chat history and handle user inputs efficiently.Document Loaders and RetrievalsWork with loaders for web pages, PDFs, Google Drive, and WhatsApp data.Retrieve and summarize documents, convert text data, and use vector stores.Vector Stores and RetrievalsIntegrate vector stores for document retrieval using FAISS and Chroma.Reload retrievers, index documents, and enhance retrieval accuracy.Tool Calling and Custom AgentsSet up tools for Tavily Search, PubMed, Wikipedia, and more.Design custom agents that can use these tools and execute step-by-step instructions.Real-World IntegrationsExecute text-based queries on MySQL .Who This Course Is ForDevelopers and data scientists who want to use Langchain and Ollama for AI applications.AI enthusiasts looking to automate workflows and create document retrieval systems.Professionals needing to build end-to-end chatbots or deploy applications on AWS.Learners with basic Python knowledge who want practical experience with real-world AI tools.By the end of this course, you'll have the skills to build, deploy, and manage AI-powered applications, from chatbots to document retrievers, ready for production.
Overview
Section 1: Introduction
Lecture 1 Install Ollama
Lecture 2 Touch Base with Ollama
Lecture 3 Inspecting LLAMA 3.2 Model
Lecture 4 LLAMA 3.2 Benchmarking Overview
Lecture 5 What Type of Models are Available on Ollama
Lecture 6 Ollama Commands - ollama server, ollama show
Lecture 7 Ollama Commands - ollama pull, ollama list, ollama rm
Lecture 8 Ollama Commands - ollama cp, ollama run, ollama ps, ollama stop
Lecture 9 Create and Run Ollama Model with Predefined Settings
Lecture 10 Ollama Model Commands - /show
Lecture 11 Ollama Model Commands - /set, /clear, /save_model and /load_model
Lecture 12 Ollama Raw API Requests
Lecture 13 Load Uncesored Models for Banned Content Generation[Only Educational Purpose]
Section 2: Getting Started with Langchain
Lecture 14 Langchain Introduction
Lecture 15 Lanchain Installation
Lecture 16 Langsmith Setup of LLM Observability
Lecture 17 Calling Your First Langchain Ollama API
Lecture 18 Generating Uncensored Content in Langchain[Educational Purpose]
Lecture 19 Trace LLM Input Output at Langsmith
Lecture 20 Going a lot Deeper in the Langchain
Section 3: Chat Prompt Templates
Lecture 21 Why We Need Prompt Template
Lecture 22 Type of Messages Needed for LLM
Lecture 23 Circle Back to ChatOllama
Lecture 24 Use Langchain Message Types with ChatOllama
Lecture 25 Langchain Prompt Templates
Lecture 26 Prompt Templates with ChatOllama
Section 4: Chains
Lecture 27 Introduction to LCEL
Lecture 28 Create Your First LCEL Chain
Lecture 29 Adding StrOutputParser with Your Chain
Lecture 30 Chaining Runnables (Chain Multiple Runnables)
Lecture 31 Run Chains in Parallel Part 1
Lecture 32 Run Chains in Parallel Part 2
Lecture 33 How Chain Router Works
Lecture 34 Creating Independent Chains for Positive and Negative Reviews
Lecture 35 Route Your Answer Generation to Correct Chain
Lecture 36 What is RunnableLambda and RunnablePassthrough
Lecture 37 Make Your Custom Runnable Chain
Lecture 38 Create Custom Chain with chain Decorator
Section 5: Output Parsing
Lecture 39 What is Output Parsing
Lecture 40 What is Pydantic Parser
Lecture 41 Get Pydantic Parser Instruction
Lecture 42 Parse LLM Output Using Pydantic Parser
Lecture 43 Parsing with `.with_structured_output()` method
Lecture 44 JSON Output Parser
Lecture 45 CSV Output Parsing - CommaSeparatedListOutputParser
Lecture 46 Datetime Output Parsing
Section 6: Chat Message Memory | How to Keep Chat History
Lecture 47 How to Save and Load Chat Message History (Concept)
Lecture 48 Simple Chain Setup
Lecture 49 Chat Message with History Part 1
Lecture 50 Chat Message with History Part 2
Lecture 51 Chat Message with History using MessagesPlaceholder
Section 7: Make Your Own Chatbot Application
Lecture 52 Introduction
Lecture 53 Introduction To Streamlit and Our Chat Application
Lecture 54 Chat Bot Basic Code Setup
Lecture 55 Create Chat History in Streamlit Session State
Lecture 56 Create LLM Chat Input Area with Streamlit
Lecture 57 Update Historical Chat on Streamlit UI
Lecture 58 Complete Your Own Chat Bot Application
Lecture 59 Stream Output of Your Chat Bot like ChatGPT
Section 8: Document Loaders | Projects on PDF Documents
Lecture 60 Introduction to PDF Document Loaders
Lecture 61 Load Single PDF Document with PyMuPDFLoader
Lecture 62 Load All PDFs from a Directory
Lecture 63 Combine All PDFs Data as Context Text
Lecture 64 How Many Tokens are There in Contex Data.
Lecture 65 Make Question Answer Prompt Templates and Chain
Lecture 66 Ask Questions from Your PDF Documents
Lecture 67 Summarize Your PDF Documents
Lecture 68 Project 3 - Generate Detailed Structured Report from the PDF Documents
Section 9: Document Loaders | Stock Market News Report Generation
Lecture 69 Introduction to Webpage Loaders
Lecture 70 Load Unstructured Stock Market Data
Lecture 71 Make LLM QnA Script
Lecture 72 Catastrophic Forgetting of LLM
Lecture 73 Break Down Large Text Data Into Chunks
Lecture 74 Create Stock Market News Summary for Each Chunks
Lecture 75 Generate Final Stock Market Report
Section 10: Document Loaders | Microsoft Office Files Reader and Projects
Lecture 76 Introduction to Unstructured Data Loader
Lecture 77 Load .PPTX Data with DataLoader
Lecture 78 Process .PPTX data for LLM
Lecture 79 Generate Speaker Script for Your .PPTX Presentation
Lecture 80 Loading and Parsing Excel Data for LLM
Lecture 81 Ask Questions from LLM for given Excel Data
Lecture 82 Load .DOCX Document and Write Personalized Job Email
Section 11: Document Loaders | YouTube Video Transcripts and SEO Keywords Generator
Lecture 83 Load YouTube Video Subtitles
Lecture 84 Load YouTube Video Subtitles in 10 Mins Chunks
Lecture 85 Generate YouTube Keywords from the Transcripts
Section 12: Vector Stores and Retrievals
Lecture 86 Introduction to RAG Project
Lecture 87 Introduction to FAISS and Chroma Vector Database
Lecture 88 Load All PDF Documents
Lecture 89 Recursive Text Splitter to Create Documents Chunk
Lecture 90 How Important Chunk Size Selection is?
Lecture 91 Get OllamaEmbeddings
Lecture 92 Document Indexing in Vector Database
Lecture 93 How to Save and Search Vector Database
Section 13: RAG | Question Answer Over the Health Supplements Data
Lecture 94 Load Vector Database for RAG
Lecture 95 Get Vector Store as Retriever
Lecture 96 Exploring Similarity Search Types with Retriever
Lecture 97 Design RAG Prompt Template
Lecture 98 Build LLM RAG Chain
Lecture 99 Prompt Tuning and Generate Response from RAG Chain
Section 14: Tool and Function Calling
Lecture 100 What is Tool Calling
Lecture 101 Available Search Tools at Langchain
Lecture 102 Create Your Custom Tools
Lecture 103 Bind tools with LLM
Lecture 104 Working with Tavily and DuckDuckGo Search Tools
Lecture 105 Working with Wikipedia and PubMed Tools
Lecture 106 Creating Tool Functions for In-Built Tools
Lecture 107 Calling Tools with LLM
Lecture 108 Passing Tool Calling Result to LLM Part 1
Lecture 109 Passing Tool Calling Result to LLM Part 2
Section 15: Agents
Lecture 110 How Agent Works
Lecture 111 Tools Preparation for Agent
Lecture 112 More About the Agent Working Process
Lecture 113 Selection of Prompt for Agent
Lecture 114 Agent in Action
Section 16: Text to MySQL Queries | With and Without Agents
Lecture 115 Create MySQL Connection with Local Server
Lecture 116 Get MySQL Execution Chain
Lecture 117 Correct Malformed MySQL Queries Using LLM
Lecture 118 MySQL Query Chain Execution
Lecture 119 MySQL Query Execution with Agents in LangGraph
Developers aiming to integrate language models into applications.,Data scientists interested in automating workflows and leveraging document retrieval.,AI enthusiasts eager to build custom chatbots and conversational tools.,Professionals seeking skills in deploying applications on AWS and other platforms.,Learners with basic Python and API knowledge who want to create end-to-end AI solutions.
Homepage
Код:
https://www.udemy.com/course/ollama-and-langchain/


Код:
Rapidgator
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Design A Fantasy Book Cover In Procreate

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Free Download Design A Fantasy Book Cover In Procreate
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.06 GB | Duration: 0h 32m
Follow my process to create a stunning cover design, with no art skills required

What you'll learn
Designing an eBook cover in Procreate
Working from a Procreate brushset (provided)
The Fantasy book genre, fantasy sub-genres, and some famous (and not so famous) examples
Finding cover inspiration
Defining characteristics of fantasy covers
Choosing the right fonts for your fantasy cover
Applying finishing touches to make your cover pop
Requirements
You should have an iPad and the Procreate app
A stylus or Apple pencil is highly recommended
A basic knowledge of Procreate is helpful, but not required
No artistic skills necessary
Description
Have you ever wanted to design a fantasy book cover, but didn't know how to start? Join illustrator and book cover designer Doni Waikel for an in-depth class into creating fantasy book covers in Procreate!From inspiration to final design, Doni takes you on a journey into the magical world of fantasy book covers. First, you'll learn about the fantasy genre and how to find design ideas, then follow along as Doni reveals her full process for creating a fantasy cover from scratch, in Procreate. In this class, you'll learn about:The fantasy book genre, fantasy sub-genres, and some famous (and not famous) examplesFinding cover inspirationDefining characteristics of fantasy coversUsing a brushsetApplying finishing touches to make your design popThe best thing about this class? You don't have to be a professional illustrator. I'll be using a Procreate brushset (supplied) to create a demo cover, and I'll walk you through the process on how to create a stunning cover design with minimal effort.Included in this class is my Fantasy Starter Kit, which includes:Fantasy Cover Brushset (lite version)Oseberg font, a copyright-free font for commercial and personal useThe exact color palette I use in the tutorialWhatever fantasy subgenre you're into, this class will give you the tools and confidence to create a cover that grabs attention and resonates with readers.Grab your iPad and pencil, find a cozy chair or sofa, and let's get started!
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 What is Fantasy?
Lecture 3 Fantasy Cover Inspiration
Lecture 4 Designing a Fantasy Cover 101
Lecture 5 Follow-Along Tutorial
Lecture 6 Class Project
Lecture 7 Final Thoughts
Self-✅Publishers who want to learn how to create their own fantasy book covers,Graphic designers who want to learn more about designing book covers
Homepage
Код:
https://www.udemy.com/course/fantasy_book_cover_procreate/


Код:
Rapidgator
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Design Like A Pro - Figma Tokens For Effective Design Systems

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Free Download Design Like A Pro - Figma Tokens For Effective Design Systems
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 343.11 MB | Duration: 0h 59m
Master Figma Tokens to Build Consistent and Scalable Design Systems for Seamless Collaboration and Efficiency

What you'll learn
Managing Design Tokens
Using Primitive Tokens
Explore Semantic Tokens
Token Structuring and Organization
Typography and Spacing Tokens
Naming Conventions for Tokens
Radius and Component Tokens
Apply Design Tokens in Your Workflow
Requirements
No prior knowledge of tokens is required
Basic understanding of Figma is helpful.
Description
Unlock the power of Figma design tokens and transform the way you build and scale design systems! In this course, you will learn how to create and manage design tokens to ensure consistency, efficiency, and flexibility in your projects. Whether you're a seasoned designer or just getting started, this course will provide you with actionable insights on leveraging Figma tokens for better control over typography, colors, spacing, and variants. What You Will Learn:How to set up design tokens in Figma for seamless design management.Best practices for naming, organizing, and applying tokens to your design system.Ways to improve your design workflow by creating reusable tokens for typography, colors, and spacing. Course OutlinePrimitive TokensMove your tokensSemantic tokenSemantic token practiceNaming design tokensTypography-tokensSpacing TokensToken ManagementRadius TokensComponent Design TokensCreate component tokensWhy Take This Class: This course will help you streamline your design process and maintain consistency across multiple projects and teams. With design tokens, you can create scalable solutions that make updating and maintaining designs easier than ever.Who This Class is For: Ideal for UI/UX designers, product designers, Design System Managers, Figma Enthusiasts, Design Team Leaders and Managers, Design Students and Beginners who are looking to improve efficiency and standardize their design process with tokens in Figma. No prior knowledge of tokens is required, but a basic understanding of Figma is helpful.Materials Needed: Access to Figma is required, along with any basic design tools you already use. All materials and templates will be provided during the course.
Overview
Section 1: Figma Design Tokens
Lecture 1 Introduction
Lecture 2 Practice Files
Lecture 3 What is Design Tokens
Lecture 4 Primitive Tokens
Lecture 5 Move Primitive Tokens Workaround
Lecture 6 Semantic Token
Lecture 7 Semantic Token Practice
Lecture 8 Token Naming
Lecture 9 Variant and Sizing
Lecture 10 Typography Tokens
Lecture 11 Spacing Tokens
Lecture 12 Token Management
Lecture 13 Radius Tokens
Lecture 14 Component Design Tokens
Lecture 15 Create Component Tokens
Lecture 16 Bulk Rename
Lecture 17 Thank you
UI/UX Designers,Product designer,Design System Managers,Figma Enthusiasts,Design Team Leaders and Managers,Design Students and Beginners
Homepage
Код:
https://www.udemy.com/course/design-like-a-pro-figma-tokens-for-effective-design-systems/


Код:
Rapidgator
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Design Patterns and Conditional Access App Control in C#

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Free Download Design Patterns and Conditional Access App Control in C#
Published 11/2024
Created by Harsha Vardhan Govind
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 7 Lectures ( 55m ) | Size: 618 MB

Learn the modern implementation of design patterns and CAP in C#
What you'll learn
Recognize and apply design patterns in C#
Learn about applicability and usability of design patterns in C#
Learn the fundamentals of C# and .NET Framework
Learn identity Platform API in C#
Requirements
You need to have Visual Studio to be installed in your system.
Description
C# is a modern, object-oriented programming language developed by Microsoft as part of its .NET framework. Known for its versatility, C# is commonly used in a range of applications, including web, desktop, and mobile software development. Understanding C# basics is essential for any beginner aiming to dive into software development within the Microsoft ecosystem.C# follows a syntax similar to languages like Java and C++, making it relatively accessible for those with experience in similar languages. The basic building blocks of a C# program are classes and objects. Classes define the blueprint for objects, while objects represent instances of classes. C# is highly object-oriented, and thus every program relies on defining classes and using methods and properties to manipulate the data encapsulated within them. The language is statically typed, meaning that all variables must have their types defined at the time of declaration. C# provides various primitive data types, such as int, double, char, and string, for representing numerical, character, and textual data.C# combines the power of object-oriented programming with robust language features, making it an ideal choice for developers across various domains. Mastering its basics enables a strong foundation for creating complex, scalable applications within the .NET framework.
Who this course is for
Anyone interested in learning design patterns in C#
Homepage
Код:
https://www.udemy.com/course/design-patterns-and-conditional-access-app-control-in-c/




Код:
Rapidgator
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Design Thinking + ChatGPT For Beginners & Business

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Free Download Design Thinking + ChatGPT | For Beginners & Business
Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 24m | Size: 1.65 GB
Enhance your skills to innovate, solve problems creatively at work with ChatGPT + 6-STEP D.E.S.I.G.N Thinking Framework

What you'll learn
Understand what is Design Thinking and how the Design Thinking process works
Apply the 6-Step Design Thinking Framework to creatively solve simple-to-complex problems
A step-by-step process for creating and testing a new idea or improving a product or service
Using AI in Design Thinking can inspire you to think outside the box & address problems more effectively.
Write effective prompts to ensure ChatGPT responses are aligned with the task at hand, streamlining the process & be more efficient
Enhance innovation and creativity within your organization
Gain insights into your users' or customers' perspectives to address their needs
Unlocking the Creative Power: Overcoming Self-Doubt, Self-Sabotage & Embracing a Growth Mindset in Design Thinking
Set clear objectives for your design research initiatives
Conduct design research including target user interviews and synthesize insights
Lead effective brainstorming sessions to generate innovative ideas
Develop and test prototypes early to minimize risk plus avoid spending too much time, investment & resources
Why Desirability, Viability & Feasibility is important?
Create a plan to iterate and refine your ideas & prototypes continuously
Develop & manage the entire Design Thinking project & pitch ideas confidently to Investors & Clients
Embrace the power of taking action, and see your vision come to life, bringing positive change, success & endless possibilities.
Requirements
No prerequisites required
Description
Are you having a challenging problem at work and do not have any solution?Have you ever felt lost and confused, unsure where to begin or which business direction to take?You have an amazing idea for a new product or service but are unsure if the market is ready for it - feasible & viable to launch?Don't fret! Design Thinking can help you solve your problems through its proven methodology.Our 6-STEP D.E.S.I.G.N Design Thinking is structured, yet flexible and focuses on human-centered problem-solving.Why do we need to first begin with 'D' = Define?Starting with Define helps you or your team to clearly articulate what needs to be solved, ensuring that the subsequent Empathy phase is laser-focused on gathering relevant and actionable user insights from the right target users.In addition, knowing the problem you are tackling helps you empathize with the right audience and focus on relevant aspects of their experiences.This course material follows a streamlined 6-step Design Thinking methodology that is both simple and easy to understand. It introduces the core principles of Design Thinking and clearly shows how this methodology can provide value to you and your company, without any fluff or frills.It offers practical ways to apply it to your work, ie. whether you are a beginner in Design Thinking or even a seasoned practitioner, you will find value here.Best of all, Design Thinking isn't limited to just one profession or industry - it can be applied to any field, from IT, Marketing, Finance, or Logistics to Product Development to Service improvement.Regardless of your role, Design Thinking can help you find the solutions to the problems you face.The course is designed to be hands-on. Therefore, you will spend time working on your Design Thinking project, allowing you to put theory into practice and apply what you are learning to a real-world challenge.You will also receive a Guidebook plus templates to guide you through each phase of the process.Using AI as your 24/7 assistant, you can leverage AI (ChatGPT) to explore multiple angles, refine solutions & ultimately propose better solutions & products. With the help of AI, you can better understand Design Thinking concepts, while businesses can apply these principles to real-world challenges without extensive prior knowledge.Discover creative solutions and make an impact on your organization and your users' experiences.Enroll now. Let's Go!
Who this course is for
Product Managers & Designers
Managers, Team Leaders & Business Owners
Having a challenging problem at work and do not have any solution
Feeling overwhelmed and lost, not knowing where to start or which business direction to choose
Have an amazing idea for a new product or service but unsure if the market is ready for it - feasible & viable to launch?
Homepage
Код:
https://www.udemy.com/course/design-thinking-chatgpt-for-beginners-business/



Код:
Rapidgator
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Design User Interface for LinkedIn & Amazon with Figma

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Free Download Design User Interface for LinkedIn & Amazon with Figma
Last updated 10/2024
Created by Boroji Design Inc.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 33 Lectures ( 4h 31m ) | Size: 1.8 GB

Advanced fast-paced Figma course for UI UX Design, User Experience Design, User Interface Design & Web Design
What you'll learn
Transform your static components into interactive UI elements
Design complex nested components with Auto Layout & Variants
Learn automated ways to re-use components & utilize Figma plugins
Learn how to design Figma UI components with blazing speed
Add Amazon & LinkedIn Figma projects to your design portfolio
Learn Figma in an advanced accelerated path
Requirements
Solid understanding of Figma
Description
By completing this advanced accelerated Figma course, you will feel confident adding 2 real world projects like Amazon & LinkedIn to your portfolio.The course is suitable for students who have a solid foundation in Figma. Students who are already familiar with Figma can greatly benefit from this course by learning cutting edge Figma skills. At the beginning of each section, you will have the full access to download the Figma source files. We will dive right into designing projects in no time.Amazon Project:Design scalable and reusable color systems Breakdown the Amazon project into smaller UI components and re-use them in FigmaCreate a prototype in Figma by combining Amazon UI componentsLearn how to sync data to your Amazon UI components LinkedIn Project:Design LinkedIn UI components with Auto Layout and VariantsCombine LinkedIn UI components into a working prototype in FigmaTransform static components into interactive componentsLearn how to re-use components & styles to design the LinkedIn project efficientlyOther important topics that you will learn:Design complex Figma auto layouts and nested interactive componentsGenerate color palettes and typographic items in a automated wayUtilize Figma plugins to improve your design workflowLearn how to design and deliver better products with blazing speedBuild enterprise level design systems and UI componentsLearn how to resolve UI issues as we build the components and prototypes togetherSummary of Udemy Student Review:Raguram Raju - "If you are looking for advanced prototyping in Figma this is the exact one which you need to undergo" ⭐⭐⭐⭐⭐Neil Pinnock - "I haven't finished the course yet, but this is jam packed with a lot of instruction on how to utilise components, nested components, auto layout and prototyping. Also not forgetting a effective design system. But word to the wise this is definitely a advanced course, so Hossein moves faster than you maybe used to (I would learn basics first), but he's helpful on answering any questions you may have. Highly recommended!" ⭐⭐⭐⭐⭐
Who this course is for
Intermediate Figma designers
Homepage
Код:
https://www.udemy.com/course/linkedin-amazon/




Код:
Rapidgator
https://rg.to/file/3d2d3f78a159d619c766dc9a2f84a313/khztf.Design.User.Interface.for.LinkedIn..Amazon.with.Figma.part2.rar.html
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Designing And Facilitating Diversity Training

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Free Download Designing And Facilitating Diversity Training
Published 11/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.48 GB | Duration: 2h 10m
Key Facilitation Skills for Coaches, Trainers, and Practitioners

What you'll learn
Understand the foundational concepts of diversity and inclusion training.
Identify and evaluate both the enablers and barriers within your organization that impact the effectiveness of DEl training programs.
Design DEI training that aligns with your organization's strategic goals and addresses the specific needs of your audience.
Manage diverse group dynamics effectively, enhance emotional intelligence, and navigate challenging situations during DEl training sessions.
Design and facilitate DEI workshops based on real-world scenarios provided in the course, enhancing your practical skills in a controlled environment.
Learn strategies to maintain and build upon the momentum of DEl initiatives post-training to ensure long-term impact and sustainability.
Reflect on the knowledge gained, understand the next steps, and prepare to implement DEI training effectively in your own or client
Requirements
Basic DEI Knowledge: Entrants should have a foundational grasp of diversity, equity, and inclusion principles to facilitate deeper exploration of these topics.
DEI or Facilitation Experience: Ideal for those with experience in facilitation, coaching, program administration who are looking to deepen their impact.
Workshop Participation: Previous participation in workshops is beneficial for understanding diverse educational settings and learning dynamics.
Adult Learning Design Skills: Experience in designing learning experiences for adults.
Openness and Reflectivity: A commitment to self-exploration, bias examination, and engagement in reflective practices enhances the learning journey.
Technical Requirements: Reliable internet access and suitable technology (computer or tablet) are essential for full course participation.
Description
This course equips professionals with essential skills to design, facilitate, and sustain impactful training programs. Participants will learn to assess organizational enablers and barriers to DEI initiatives, design tailored workshops that align with organizational strategies, and manage group dynamics to foster productive learning environments. Through a comprehensive curriculum that includes case studies, real-world scenarios, and practical exercises, learners will gain expertise in adapting training to various learning styles and leveraging data to maximize DEI outcomes.The course begins with foundational knowledge, focusing on assessing organizational readiness and identifying critical factors that influence DEI training success. Moving into the design phase, learners explore best practices for creating DEI workshops that drive both individual and organizational growth, supported by worksheets and activities. The facilitation section hones participants' skills in managing challenging group dynamics and responding to sensitive issues with emotional intelligence.In the practice section, participants engage with detailed case studies, tackling scenarios related to legislation, social tensions, and leadership challenges, helping them to apply their skills in realistic contexts. The course concludes by addressing the importance of post-training sustainability and strategies to maintain DEI momentum within organizations.This course is ideal for DEI facilitators, HR professionals, and organizational leaders who want to make a meaningful impact in promoting diversity and fostering inclusion in their organizations.
Overview
Section 1: Introduction
Lecture 1 Meet Your Instructor
Lecture 2 Learning Objectives
Section 2: Assessing Organization Enablers and Barriers to DEI Training
Lecture 3 Assessing the Organization Enablers to Your Diversity and Inclusion Training
Lecture 4 Assessment - Organizational Enablers
Lecture 5 Assessing the Organization Barriers to Your Diversity and Inclusion Training
Lecture 6 Assessment - Organizational Barriers
Lecture 7 Assessing System-Level Factors for Effective DEI Workshop Design
Lecture 8 Assessment - DEI System-Level Practices
Lecture 9 Navigating Informal Organizational Norms
Lecture 10 Evaluating Internal Support for Your Training Initiative
Lecture 11 Assessment - Support Evaluation
Lecture 12 Shaping DEI Training with Data and Sensitivity
Lecture 13 Assessment - Leveraging Internal Data
Lecture 14 Conclusion Assessing Organization Enablers to DEI Training - Conclusion
Section 3: Designing Diversity Training
Lecture 15 Designing and Facilitating Diversity Training: What You'll Learn
Lecture 16 Designing Training with Organizational Strategy: First Three S's
Lecture 17 Facilitating Training for Individual and Organizational Growth: Last Four S's
Lecture 18 Learning the ABCs of DEI Workshops: A Comprehensive Guide
Lecture 19 Building on Existing Training: Leveraging and Amplifying Organizational Training
Lecture 20 Worksheet - Building on Existing Training
Lecture 21 Tailoring Learning Styles for Your Organization's DEI Initiatives
Lecture 22 Optimizing Learning Aids for Effective DEI Training
Lecture 23 Designing Diversity Training: Conclusion
Section 4: Facilitating and Managing Group Dynamics in Training Programs
Lecture 24 The Facilitator's Role in DEI Training
Lecture 25 Enhancing Emotional Intelligence for Effective DEI Facilitation
Lecture 26 How to Navigate Challenging Classroom Situations
Lecture 27 Avoiding Facilitator Pitfalls
Lecture 28 Framework for Group Dynamics in DEI Training
Lecture 29 How Learners Show Up: What Learners Bring to DEI Experiences
Lecture 30 Managing Behaviors in DEI Workshops
Lecture 31 Facilitator Collaboration: Maximizing Workshop Impact for DEI
Lecture 32 Facilitating and Managing Group Dynamics: Conclusion
Section 5: Designing Diversity Workshops: Practice and Application
Lecture 33 Introduction: Global Entertainment and Sports Inc.
Lecture 34 Lean About Global Entertainment and Sports Inc.
Lecture 35 Scenario 1: Responding to Legislation Conflict
Lecture 36 Scenario 2: Navigating Unexpected National Events in DEI Initiatives
Lecture 37 Scenario 3: Bridging Divides in a Polarized Environment
Lecture 38 Scenario 4: Bridging Divides with Dialogue
Lecture 39 Scenario 5: Navigating External Pressures with the Leadership Team
Lecture 40 Tips and Considerations for Designing a One-Hour DEI Workshop
Lecture 41 Designing a One-Hour DEI Workshop: Conclusion
Section 6: Sustainability and What to do After a Training
Lecture 42 Strategies for Sustaining Inclusion and Equity in Challenging Times
Section 7: Summary and Conclusion
Lecture 43 Conclusion of Designing and Facilitating Diversity Training
This course is tailored for individuals who facilitate in the DEI space however the principles in this course apply to anyone wanting to improve their facilitation, coaching, or program development skills. Ideal participants include HR professionals, team leaders, organizational development specialists, DEI practitioners, coaches and anyone interested in deepening their understanding of DEI design and facilitation.
Homepage
Код:
https://www.udemy.com/course/designing-and-facilitating-diversity-training/


Код:
Rapidgator
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Designing Creature Makeup for Film in Photoshop - Concept Design Techniques using ...

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Free Download Designing Creature Makeup for Film in Photoshop - Concept Design Techniques using ...
Johnny Fraser-Allen | Duration: 4:11 h | Video: H264 1920x1080 | Audio: AAC 44,1 kHz 2ch | 1,36 GB | Language: English
Designing makeup concepts for film and television is an important skill set for concept artists at the Wētā Workshop in New Zealand, known for decades of groundbreaking work. Join Senior Concept Designer Johnny Fraser-Allen as he shares his Photoshop techniques to effectively design character and creature makeups in this four hour workshop, with tips aimed at artists of all levels.
This detailed workshop will teach you how to deliver and lock down approved designs for the film industry. Aimed at the early stages of a production, the Photoshop-based techniques covered will allow for quick ideas to be delivered to the director as well as tackling quick changes needed to rework designs into alternate options for the same brief.
Starting with a quick warm up, Johnny goes through the steps required to build an original creature makeup design, before starting on three Ogre Lord concepts over the same actor. This same process is how he designed and reworked director notes for the BFG for Steven Spielberg, dwarves for Peter Jackson, and goblins for the Jim Henson Company.

Chapter 1: Introduction to Creature Feature Makeup Design: Johnny shares his thoughts on a career in designing characters and makeup concepts for blockbuster films and gives insight into the thought process behind the many makeup concepts he designed for The Portable Door.
Chapter 2: Warm-up with a Quick Goblin Makeup Concept: Using Jeffery Walker, the Director for The Portable Door, Johnny revisits how he designed Goblin makeup for Sam Neil and others in a quick warm-up session.
Chapter 3: Sketching: Johnny shows how a quick sketch - that no one will ever see but the artist - can help speed up the design process and inform some helpful starting points that will lead to the happy accidents found in the final design.
Chapter 4: The Concept Art: Creating his own brief of "Ogre King," Johnny goes through every step he uses to take a photo of the production's chosen actor and work up three original makeup concepts to turn him into the creature required for filming. With an emphasis on practicality and retaining the qualities of the performer beneath, this tutorial shows how to use the shapes and existing textures of the actor as well as incorporating other photographic elements to help shape a realistic, filmic-looking concept design using only Photoshop. This then serves as the initial discussion point used to get the ball rolling for the director of the film.
Homepage
Код:
https://www.thegnomonworkshop.com/tutorials/designing-creature-makeup-for-film-in-photoshop



Код:
Rapidgator
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Designing Effective Employee Onboarding Programs

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Free Download Designing Effective Employee Onboarding Programs
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 195.26 MB | Duration: 0h 38m
Strategies for Creating a Seamless Onboarding Experience That Drives Engagement, Retention, and Productivity

What you'll learn
Fundamentals of Onboarding: Understanding the importance of onboarding, its objectives, and how it differs from orientation.
Creating a Structured Onboarding Journey: How to design a step-by-step onboarding process that includes preboarding, initial orientation, role-specific training
Preboarding and Orientation Best Practices: Techniques for engaging new hires before their first day, creating a welcoming environment, and providing effective
Role-Specific Training and Development: How to create tailored training programs that equip new hires with the skills and knowledge needed for their specific ro
Integration and Socialization: Strategies for helping new hires integrate into the team and company culture, including mentorship programs, team-building activi
Performance Management and Feedback: Best practices for setting clear performance expectations, providing constructive feedback, and using performance metrics t
Legal and Compliance Considerations: Key legal aspects of onboarding, including workplace safety, anti-harassment policies, and documentation requirements, to e
Leveraging Technology in Onboarding: How to use onboarding software, learning management systems, and collaboration tools to streamline the process and enhance
Evaluation and Continuous Improvement: Techniques for assessing the effectiveness of the onboarding program through feedback, data analysis, and making iterativ
By the end of the course, students will be equipped with the skills to design, implement, and evaluate a comprehensive onboarding program that supports new hire
Requirements
Basic Understanding of HR Concepts: While the course is designed to be accessible, a foundational knowledge of human resources concepts such as employee lifecycle, recruitment, and employee engagement will be helpful.
Experience in HR or Management Roles: This course is particularly suited for HR professionals, hiring managers, and team leaders who are directly involved in the hiring and onboarding processes.
Interest in People Management: A genuine interest in improving the onboarding experience and supporting new hires is crucial for applying the concepts taught in the course.
Access to a Computer and Internet: Since the course may involve using online platforms and tools for training and assignments, having access to a computer with an internet connection is necessary.
Willingness to Engage in Practical Applications: The course includes exercises and case studies that require participants to apply the principles to real-world scenarios. A readiness to actively participate in these practical applications will enhance the learning experience.
Basic Understanding of Technology Tools (Recommended): Familiarity with software tools such as learning management systems (LMS), onboarding software, or collaboration tools like Zoom, Microsoft Teams, or Slack can be advantageous when exploring the technology component of the course.
No specific certifications or degrees are required to enroll, making this course suitable for anyone with a desire to enhance their onboarding skills and create a welcoming, effective environment for new hires.
Description
Designing Effective Employee Onboarding Programs is a comprehensive course designed to equip HR professionals, hiring managers, team leaders, and business owners with the tools and strategies needed to create a successful onboarding experience. This course covers every stage of the onboarding journey, from preboarding and initial orientation to role-specific training, integration, and performance management.Through a mix of engaging lessons, real-world examples, and practical exercises, you'll learn how to design an onboarding process that not only welcomes new hires but also sets them up for long-term success within your organization. You will discover the importance of aligning your onboarding program with company culture, providing ongoing support, and using feedback to continuously improve the process.Additionally, you'll explore how to leverage technology and tools to streamline onboarding activities and create a dynamic, engaging experience for new employees. By the end of the course, you will have the skills to create a tailored onboarding program that reduces turnover, increases productivity, and ensures that new hires feel valued and integrated into their roles.Whether you're looking to revamp an existing onboarding program or build one from scratch, this course provides the insights and guidance you need to create an impactful onboarding experience that benefits both new hires and your organization.
Overview
Section 1: Introduction
Lecture 1 introduction to onboarding
Lecture 2 Understanding Onboarding
Lecture 3 Phases of Onboarding
Lecture 4 Preboarding
Lecture 5 Orientation Essentials
Lecture 6 Engaging New Employees
Lecture 7 Developing a Training Plan
Lecture 8 Mentorship and Buddy Systems
Lecture 9 Ongoing Support and Feedback
Lecture 10 Evaluating the Onboarding Program
Section 2: 1.2 The Onboarding journey
Lecture 11 The Onboarding Journey
Lecture 12 Preboarding Phase
Lecture 13 Orientation Phase
Lecture 14 Integration Phase
Lecture 15 Preboarding Activities
Lecture 16 Orientation Day 1
Lecture 17 Company Culture and Values
Lecture 18 Initial Training and Development
Lecture 19 Mentorship and Buddy System
Lecture 20 Continuous Support and Feedback
Section 3: Preparing for the New Employee
Lecture 21 Introduction to Preboarding
Lecture 22 Initial Communication
Lecture 23 Document Preparation
Lecture 24 Workspace Setup
Lecture 25 Preboarding Packet
Lecture 26 Virtual Introductions
Lecture 27 Setting Expectations
Lecture 28 Providing Resources
Lecture 29 Preboarding Checklist
Lecture 30 Feedback and Continuous Improvement
Section 4: Creating a Welcoming Environment
Lecture 31 Creating a Welcoming Environment
Lecture 32 Preparing the Workspace
Lecture 33 Welcome Package
Lecture 34 Office Tour
Lecture 35 Introduction to Company Culture
Lecture 36 Assigning a Buddy or Mentor
Lecture 37 Setting Up Technology
Lecture 38 Providing Essential Information
Lecture 39 First Day Agenda
Lecture 40 Feedback and Continuous Improvement
Section 5: Designing the Orientation Program
Lecture 41 Introduction to Role-Specific Training
Lecture 42 Understanding Job Descriptions
Lecture 43 Skill Assessment
Lecture 44 Developing Training Materials
Lecture 45 On-the-Job Training
Lecture 46 Mentorship Programs
Lecture 47 Continuous Learning and Development
Lecture 48 Performance Evaluation
Lecture 49 Adapting to Different Learning Styles
Lecture 50 Measuring Training Effectiveness
Section 6: Engaging New Employees
Lecture 51 Overview of Onboarding Checklists
Lecture 52 Pre-Arrival Preparations
Lecture 53 First-Day Activities
Lecture 54 Initial Training Sessions
Lecture 55 Assigning a Buddy or Mentor
Lecture 56 Regular Check-ins
Lecture 57 Team Integration
Lecture 58 Performance Goals
Lecture 59 Feedback and Evaluation
Lecture 60 Continuous Improvement of Onboarding Process
HR Specialists focused on recruitment, employee engagement, or training and development, looking to refine their approach to integrating new hires into the organization.,Managers who are directly involved in bringing new team members on board and wish to improve their ability to support and integrate new hires.,Leaders responsible for overseeing new hires during their first few months who need strategies for mentoring, socialization, and team integration.,Business owners who manage their own hiring and onboarding processes and want to create structured, effective onboarding programs.,Professionals who design and implement training programs for new hires and want to integrate role-specific training with broader onboarding goals.,Administrative Staff or Office Managers who assist in the onboarding process and want to gain insights into best practices.,This course is designed for those who want to create a seamless and effective onboarding process, ensuring that new hires feel supported, understand their roles, and integrate smoothly into the organization. It is suitable for both individuals new to onboarding and those looking to refresh and expand their existing knowledge.
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