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Free Download Python Guided Project - Building Tic-Tac-Toe from Scratch
Raj Gaurav Mishra | Duration: 1:03 h | Video: HVC1 1280x720 | Audio: AAC 48 kHz 2ch | 108 MB | Language: English
For beginner Python developers curious about developing a game in Python and a portfolio project for resume.
This is an entry-level guided project and is about developing a game in Python. This course is designed for beginners who want to start their career journey in the field of IT and Software Engineering. This course is for beginner Python developers curious about developing a game in Python. In this guided project (course), we will implement a game (Tic-Tac-Toe) using Python programming. This will be an implementation of the Tic-Tac-Toe game using random numbers. To maintain simplicity, this game will be programmed to play automatically and no user input will be required.
What is Tic-Tac-Toe?

Tic-tac-toe, noughts and crosses, or Xs and Os is a paper-and-pencil game for two players who take turns marking the spaces in a three-by-three grid with X or O. The winner is the first player to get three of the same symbols in a row (up, down or diagonally).
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https://www.udemy.com/course/python-guided-project-building-tic-tac-toe-from-scratch/

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Free Download Python Mastery Devops, Automation, And Real-World Use Cases
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.23 GB | Duration: 9h 0m
From Coding Fundamentals to Cloud Automation, GitHub Integration, CI/CD Automation with Jenkins and Game Development

What you'll learn
Python coding practice
About Data Types in Python
Regular Expression (regex) in Python
How to identify and apply keywords in code
How to declare and assign values to variables.
The purpose and function of the return statement in functions.
Python Functions: Definition and Usage
Utilizing Modules in Function Design
Organizing Your Code Using Python Packages
The use of the sys module to access command line arguments
The different types of operators in Python, including arithmetic, comparison, logical, and assignment operators.
DevOps Use Cases with if..else..elif
For/While Loops in Python: Syntax and Usage
Real-time Use Case: Lists and Exception Handling in Python
Python Script for Handling Exceptions Using Try Statements
Integrating Python with GitHub Through the GitHub API
Cloning a GitHub Repository with Python
Performing operations on various AWS services like S3, EC2 using Boto3 Python Module
Launching an EC2 Instance using Boto3 Python Module
CI/CD Automation with Jenkins and Python
Integrate GitHub Webhooks With Jenkins
Develop Games in Python with PyCharm and ChatGPT
Requirements
Basic Computer Skills: Familiarity with using a computer and navigating the internet.
No Prior Programming Experience Required: This course is designed for beginners, so no previous programming knowledge is necessary.
Basic Knowledge of DevOps is required
Description
Python for DevOps means using Python to make DevOps tasks easier and more efficient. DevOps is all about automating tasks like building, testing, and deploying software quickly, as well as managing servers and infrastructure. Python is great for this because it's simple to learn, and it has many tools and libraries that help automate these tasks. For example, you can use Python to automatically create servers, manage cloud services, and set up continuous integration and delivery (CI/CD) pipelines. Python helps DevOps teams work faster and more effectively by reducing manual work and making processes smoother.Course Outline:Section1: Introduction-> Introduction-> An overview of Python-> About Shell Scripting-> Python vs. Shell Scripting-> When to Use Python vs. Shell ScriptingSection2: How to Begin Practicing Python Coding-> Begin Python Coding Practice-> Visual Studio Code - Python Coding Practice-> PyCharm - IDEs-> Codespaces - Online Coding PlatformSection3: Python Data Types-> About Data Types in Python-> Lab - String Data Type-> Lab - Integer Data Type-> Lab - Float Data Type-> Lab - len(), Length of a string-> Lab - String upper(), lower()-> Lab - String replace()-> Lab - String split()-> Lab - Print specific object in split()-> About List in Python-> Lab - List Data Type-> Lab - Add and Modify in a List Data Type (Mutable)-> About Tuples in Python-> Lab - Tuples in Python-> About Sets in Python-> Lab - Sets in Python-> Dictionary in Python-> Lab - Dictionary in Python-> Use Cases in DevOps-> Boolean Data Types-> Lab - Boolean in Python-> Coding Exercise 1:Create a Python script to add two integers-> Coding Exercise 2:Create a python script to perform operation of floating-point-> Coding Exercise 3:Write a python script to determine the length of a string-> Coding Exercise 4:Create a python script to convert a string to uppercase and lowercase-> Coding Exercise 5:Create a Simple python Script to replace a substring within a string-> Coding Exercise 6:Create a Simple python script to Split the text of a string-> Coding Exercise 7:Create a python script to define a Variable and assign it a list of five integersSection4: Regular Expression (regex) in Python-> Overview of Regular Expressions in Python-> Lab - Using re. match() to Match Patterns at the Start of a String-> Lab - Using re. search() to Find Matches Anywhere in a String-> Lab - Using re. findall() to Search for All Matches in a String-> Regex Use Cases from a DevOps Perspective-> Coding Exercise 8:Regular Expression in python-> Section5: Mastering Keywords in Python-> Overview of Keywords in Python-> Common Python keywords-> Mastering Control Flow Keywords - if, else, for, and break-> Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc.Section6: Working with Variables in Python-> Overview of Variables with Example-> Lab: Working with Float Variables in Python-> Lab: Defining Lists as Variables in Python-> Lab: Working with Dictionary Variables in Python-> Python Variables: Local vs Global Scope-> Lab: Working with Local Variables in Python-> Lab: Working with Global Variables in PythonSection7: Return Statement in Python-> Return Statement: An Overview with Syntax-> Lab: Creating Functions That Return Values-> Lab: Functions That Return Multiple Values-> Lab: Function for Identifying Even and Odd ValuesSection8: Python Functions: Definition and Usage-> Introduction to Functions in Python-> Advantages of functions in Python-> Lab: Functions with Parameters-> Lab: Functions with Return Value-> Lab: Designing Functions for Basic Arithmetic Operations-> Comparing Scripts: Using Functions vs. Not Using FunctionsSection9: Utilizing Modules in Function Design-> Introduction to Python Modules-> An Overview of Built-in Modules-> An Overview of User-defined Modules-> Lab: Essential Built-in Modules in Python-> Lab: OS and Math Modules-> Lab: Building Your Own ModulesSection 10: Python Packages: Organizing Your Code-> Introduction to Python Packages-> Key Concepts of Packages-> Advantages of Using Packages-> Lab: Creating Package Structures and Modules-> Importing Modules for Easier Access using __init__. py-> Creating a Main Python File to Utilize Your Package-> Importing Functions from a PackageSection 11: Command Line Arguments in Python-> Command Line Arguments with Practical Examples-> Lab: Script to Add Two Numbers (No Command Line Arguments)-> Lab: Working with sys. argv for Command Line Arguments-> Lab: Passing Multiple Arguments to Python Scripts-> Lab: Pass Arguments to Add Two Numbers-> Lab: Conditional Arithmetic via Script Arguments-> Lab: Conditional Arithmetic Using Script ArgumentsSection 12: Operators in Python: Concepts and Examples-> The Basics of Arithmetic Operators in Python-> Lab: Exploring Comparison (Relational) Operators-> Lab: Comparison Operators (=, >, >=, ==)-> Logical Operators: and, or, not-> Lab: Using 'and' , 'or' for Logical Operations-> Lab: Using 'not' for Logical Operations-> Assignment Operators in Python-> Lab: Understanding Different Assignment Operators-> Membership Operators: 'in' and 'not in'-> Lab: Using 'not in' Membership Operators-> Operators in DevOps: Practical Use Cases-> Use Cases for Operators in the DevOps WorkflowSection 13: Conditional Statements in Python-> Understanding 'if' statement in Python-> Understanding 'else'..'elif' statement in Python-> Lab: Implementing if..else Statements-> Lab: DevOps Use Cases with if..else..elifSection 14: Understanding Loops in Python-> For Loops in Python: Syntax and Usage-> While Loops in Python: Syntax and Usage-> Lab: Implementing For Loops-> Lab: Printing Ranges and Strings with For Loops-> Lab: Implementing Infinite While Loops-> Lab: Exploring Break Statements in PythonSection 15: Real-time Use Case: Lists and Exception Handling in Python-> Introduction to the Real-Time Project-> Lab: User Input for List Creation-> Lab: Understanding split function text.split()-> Lab: Identify modules and their functions-> Lab: Utilize a for loop to list files-> Exception Handling with Try Statement-> Lab: Python Script for Handling Exceptions Using Try Statements-> Lab: Handling Error - FileNotFoundError-> Lab: Handling Known Error - PermissionErrorSection 16: Integrating Python with GitHub-> Integrating Python with GitHub Through the GitHub API-> Lab: Install PyGithub and Generate a GitHub Access Token-> Lab: Retrieve User Login and Public Repos with Python-> Lab: Retrieve GitHub Account Repository List-> Lab: Create a New Repository with PythonSection 17: Cloning a GitHub Repository with Python-> Clone a Repository Using the Subprocess Module-> Lab: Clone a Repository with the Subprocess Module-> Lab: Using GitPython Library-> Lab: Handle Git Errors with Exception HandlingSection 18: Boto3 Python Module-> Introduction to the Boto3 Python Module-> Lab: Install Boto3 and Create an AWS User Account-> Lab: Configure GitHub Access from Codespaces via AWS CLI-> Lab: List All Buckets with Boto3-1-> Lab: List All Buckets with Boto3-2-> Lab: List All Buckets with Boto3-3-> Lab: Upload a File to a Bucket Using Boto3-> Lab: Download a File to a Bucket Using Boto3Section 19: Launching an EC2 Instance using Boto3 Python Module-> Project Overview-> Setting Up a User Account in AWS with IAM-> Set Up AWS CLI in Codespaces-> Begin Python Script: Import Boto3-> Include EC2 Attributes in Python Script-> Add Tag Specifications in Python Script-> Debug the Python Script Before Execution-> Access the EC2 Instance Launched via Python Script-> Update the Python Script to Add 20GB EBS Volume-> Run Python Script to Confirm EBS Volume-> Update Python Script to Include UserData-> Update Python Script to Include Apache Package-> Run the Revised Python Script and Validate-> Access the Apache ServerSection 20: CI/CD Automation with Jenkins and Python-> Project Overview-> Set Up a GitHub Repository for Your Project-> Write the Source Code in Python and Push to GitHub Repository-> Provision a Jenkins Server Instance in AWS-> Connect to the Jenkins Server and Install Java-> Install the Jenkins Package on the Server-> Set Up Jenkins Configuration-> Install Necessary Plugins on the Jenkins Server-> Add GitHub Credentials to the Jenkins Server-> First Stage of the Pipeline: Checkout the Project-> Build the Job-> Add a Stage for Installing Python Dependencies-> Add a Stage to Execute the Python Script-> Setting Up a User Account in AWS with IAM-> Create Access Keys for Jenkins Credentials-> Set Up Access Keys in Jenkins Pipeline-> Export AWS Credentials in Jenkins Pipeline-> Build the Job and Verify EC2 Instance Creation in AWS-> Access the Web Server Using URLSection 21: Integrate GitHub Webhooks With Jenkins-> Setup GitHub Webhooks in Jenkins-> GitHub hook trigger for GITScm polling-> Add Jenkins Webhook to GitHub Repository-> Test the Webhook by Editing the Python ScriptSection 22: Develop Games in Python with PyCharm and ChatGPT
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 An overview of Python
Lecture 3 About Shell Scripting
Lecture 4 Python vs. Shell Scripting
Lecture 5 When to Use Python vs. Shell Scripting
Section 2: How to Begin Practicing Python Coding
Lecture 6 Begin Python Coding Practice
Lecture 7 Visual Studio Code - Python Coding Practice
Lecture 8 PyCharm - IDEs
Lecture 9 Codespaces - Online Coding Platform
Section 3: Python Data Types
Lecture 10 About Data Types in Python
Lecture 11 Lab - String Data Type
Lecture 12 Lab - Integer Data Type
Lecture 13 Lab - Float Data Type
Lecture 14 Lab - len(), Length of a string
Lecture 15 Lab - String upper(), lower()
Lecture 16 Lab - String replace()
Lecture 17 Lab - String split()
Lecture 18 Lab - Print specific object in split()
Lecture 19 About List in Python
Lecture 20 Lab - List Data Type
Lecture 21 Lab - Add and Modify in a List Data Type (Mutable)
Lecture 22 About Tuples in Python
Lecture 23 Lab - Tuples in Python
Lecture 24 About Sets in Python
Lecture 25 Lab - Sets in Python
Lecture 26 Dictionary in Python
Lecture 27 Lab - Dictionary in Python
Lecture 28 Use Cases in DevOps
Lecture 29 Boolean Data Types
Lecture 30 Lab - Boolean in Python
Section 4: Regular Expression (regex) in Python
Lecture 31 Overview of Regular Expressions in Python
Lecture 32 Lab - Using re.match() to Match Patterns at the Start of a String
Lecture 33 Lab - Using re.search() to Find Matches Anywhere in a String
Lecture 34 Lab - Using re.findall() to Search for All Matches in a String
Lecture 35 Regex Use Cases from a DevOps Perspective
Section 5: Mastering Keywords in Python
Lecture 36 Overview of Keywords in Python
Lecture 37 Common Python keywords
Lecture 38 Mastering Control Flow Keywords - if, else, for, and break
Lecture 39 Lab: Mastering Control Flow Keywords - continue, def, return, class, import etc.
Section 6: Working with Variables in Python
Lecture 40 Overview of Variables with Example
Lecture 41 Lab: Working with Float Variables in Python
Lecture 42 Lab: Defining Lists as Variables in Python
Lecture 43 Lab: Working with Dictionary Variables in Python
Lecture 44 Python Variables: Local vs Global Scope
Lecture 45 Lab: Working with Local Variables in Python
Lecture 46 Lab: Working with Global Variables in Python
Section 7: Return Statement in Python
Lecture 47 Return Statement: An Overview with Syntax
Lecture 48 Lab: Creating Functions That Return Values
Lecture 49 Lab: Functions That Return Multiple Values
Lecture 50 Lab: Function for Identifying Even and Odd Values
Section 8: Python Functions: Definition and Usage
Lecture 51 Introduction to Functions in Python
Lecture 52 Advantages of functions in Python
Lecture 53 Lab: Functions with Parameters
Lecture 54 Lab: Functions with Return Value
Lecture 55 Lab: Designing Functions for Basic Arithmetic Operations
Lecture 56 Comparing Scripts: Using Functions vs. Not Using Functions
Section 9: Utilizing Modules in Function Design
Lecture 57 Introduction to Python Modules
Lecture 58 An Overview of Built-in Modules
Lecture 59 An Overview of User-defined Modules
Lecture 60 Lab: Essential Built-in Modules in Python
Lecture 61 Lab: OS and Math Modules
Lecture 62 Lab: Building Your Own Modules
Section 10: Python Packages: Organizing Your Code
Lecture 63 Introduction to Python Packages
Lecture 64 Key Concepts of Packages
Lecture 65 Advantages of Using Packages
Lecture 66 Lab: Creating Package Structures and Modules
Lecture 67 Importing Modules for Easier Access using __init__.py
Lecture 68 Creating a Main Python File to Utilize Your Package
Lecture 69 Importing Functions from a Package
Section 11: Command Line Arguments in Python
Lecture 70 Command Line Arguments with Practical Examples
Lecture 71 Lab: Script to Add Two Numbers (No Command Line Arguments)
Lecture 72 Lab: Working with sys.argv for Command Line Arguments
Lecture 73 Lab: Passing Multiple Arguments to Python Scripts
Lecture 74 Lab: Pass Arguments to Add Two Numbers
Lecture 75 Lab: Conditional Arithmetic via Script Arguments
Lecture 76 Lab: Conditional Arithmetic Using Script Arguments
Section 12: Operators in Python: Concepts and Examples
Lecture 77 The Basics of Arithmetic Operators in Python
Lecture 78 Lab: Exploring Comparison (Relational) Operators
Lecture 79 Lab: Comparison Operators (=, >, >=, ==)
Lecture 80 Logical Operators: and, or, not
Lecture 81 Lab: Using 'and' , 'or' for Logical Operations
Lecture 82 Lab: Using 'not' for Logical Operations
Lecture 83 Assignment Operators in Python
Lecture 84 Lab: Understanding Different Assignment Operators
Lecture 85 Membership Operators: 'in' and 'not in'
Lecture 86 Lab: Using 'not in' Membership Operators
Lecture 87 Operators in DevOps: Practical Use Cases
Lecture 88 Use Cases for Operators in the DevOps Workflow
Section 13: Conditional Statements in Python
Lecture 89 Understanding 'if' statement in Python
Lecture 90 Understanding 'else'..'elif' statement in Python
Lecture 91 Lab: Implementing if..else Statements
Lecture 92 Lab: DevOps Use Cases with if..else..elif
Section 14: Understanding Loops in Python
Lecture 93 For Loops in Python: Syntax and Usage
Lecture 94 While Loops in Python: Syntax and Usage
Lecture 95 Lab: Implementing For Loops
Lecture 96 Lab: Printing Ranges and Strings with For Loops
Lecture 97 Lab: Implementing Infinite While Loops
Lecture 98 Lab: Exploring Break Statements in Python
Section 15: Real-time Use Case: Lists and Exception Handling in Python
Lecture 99 Introduction to the Real-Time Project
Lecture 100 Lab: User Input for List Creation
Lecture 101 Lab: Understanding split function text.split()
Lecture 102 Lab: Identify modules and their functions
Lecture 103 Lab: Utilize a for loop to list files
Lecture 104 Exception Handling with Try Statement
Lecture 105 Lab: Python Script for Handling Exceptions Using Try Statements
Lecture 106 Lab: Handling Error - FileNotFoundError
Lecture 107 Lab: Handling Known Error - PermissionError
Section 16: Integrating Python with GitHub
Lecture 108 Integrating Python with GitHub Through the GitHub API
Lecture 109 Lab: Install PyGithub and Generate a GitHub Access Token
Lecture 110 Lab: Retrieve User Login and Public Repos with Python
Lecture 111 Lab: Retrieve GitHub Account Repository List
Lecture 112 Lab: Create a New Repository with Python
Section 17: Cloning a GitHub Repository with Python
Lecture 113 Clone a Repository Using the Subprocess Module
Lecture 114 Lab: Clone a Repository with the Subprocess Module
Lecture 115 Lab: Using GitPython Library
Lecture 116 Lab: Handle Git Errors with Exception Handling
Section 18: Boto3 Python Module
Lecture 117 Introduction to the Boto3 Python Module
Lecture 118 Lab: Install Boto3 and Create an AWS User Account
Lecture 119 Lab: Configure GitHub Access from Codespaces via AWS CLI
Lecture 120 Lab: List All Buckets with Boto3-1
Lecture 121 Lab: List All Buckets with Boto3-2
Lecture 122 Lab: List All Buckets with Boto3-3
Lecture 123 Lab: Upload a File to a Bucket Using Boto3
Lecture 124 Lab: Download a File to a Bucket Using Boto3
Section 19: Launch EC2 Instance with Boto3 Python Module
Lecture 125 Project Overview
Lecture 126 Setting Up a User Account in AWS with IAM
Lecture 127 Set Up AWS CLI in Codespaces
Lecture 128 Begin Python Script: Import Boto3
Lecture 129 Include EC2 Attributes in Python Script
Lecture 130 Add Tag Specifications in Python Script
Lecture 131 Debug the Python Script Before Execution
Lecture 132 Access the EC2 Instance Launched via Python Script
Lecture 133 Update the Python Script to Add 20GB EBS Volume
Lecture 134 Run Python Script to Confirm EBS Volume
Lecture 135 Update Python Script to Include UserData
Lecture 136 Update Python Script to Include Apache Package
Lecture 137 Run the Revised Python Script and Validate
Lecture 138 Access the Apache Server
Section 20: CI/CD Automation with Jenkins and Python
Lecture 139 Project Overview
Lecture 140 Set Up a GitHub Repository for Your Project
Lecture 141 Write the Source Code in Python and Push to GitHub Repository
Lecture 142 Provision a Jenkins Server Instance in AWS
Lecture 143 Connect to the Jenkins Server and Install Java
Lecture 144 Install the Jenkins Package on the Server
Lecture 145 Set Up Jenkins Configuration
Lecture 146 Install Necessary Plugins on the Jenkins Server
Lecture 147 Add GitHub Credentials to the Jenkins Server
Lecture 148 First Stage of the Pipeline: Checkout the Project
Lecture 149 Build the Job
Lecture 150 Add a Stage for Installing Python Dependencies
Lecture 151 Add a Stage to Execute the Python Script
Lecture 152 Setting Up a User Account in AWS with IAM
Lecture 153 Create Access Keys for Jenkins Credentials
Lecture 154 Set Up Access Keys in Jenkins Pipeline
Lecture 155 Export AWS Credentials in Jenkins Pipeline
Lecture 156 Build the Job and Verify EC2 Instance Creation in AWS
Lecture 157 Access the Web Server Using URL
Section 21: Integrate GitHub Webhooks with Jenkins
Lecture 158 Setup GitHub Webhooks in Jenkins
Lecture 159 GitHub hook trigger for GITScm polling
Lecture 160 Add Jenkins Webhook to GitHub Repository
Lecture 161 Test the Webhook by Editing the Python Script
Lecture 162 Last Lecture
Individuals with little or no prior programming experience who want to learn Python from scratch.,DevOps Professionals: Anyone interested in automation, cloud computing, and using Python for DevOps practices.,Students and Professionals: Anyone seeking to enhance their resume or career prospects by adding Python programming to their skill set.,Overall, this course is suitable for anyone eager to learn Python and apply it in real-world scenarios.
Screenshot
Homepage

https://www.udemy.com/course/pythondevops/

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Free Download Python Microservices from basics to Advanced
Published 10/2024
Created by Tharun Bonampudi
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 8 Lectures ( 54m ) | Size: 591 MB

Master how to build Python Microservices with their best practices!
What you'll learn
Learn basics and advanced concepts of Python Microservices
Learn best practices of Python Microservices
Learn python development, deployment, scaling, and management
Learn Python microservices architecture
Requirements
You need to be interested in learning Python Microservices
Description
Python microservices represent a modern software architectural approach that breaks down monolithic applications into smaller, self-contained, and loosely coupled services. Each microservice is designed to perform a specific function, and they collectively work together to form a larger, more complex application. This architecture contrasts with traditional monolithic systems, where all components are tightly integrated into a single codebase. Microservices typically communicate with each other through APIs, often using lightweight protocols like HTTP/REST or message brokers like RabbitMQ or Kafka for asynchronous communication. This decoupled nature allows services to be written in different languages, though Python is frequently chosen for its robust ecosystem and ease of use.In Python microservices, each service is responsible for its own lifecycle, including development, deployment, scaling, and management. This allows teams to work on different services independently, enabling faster development cycles and more flexible updates. One of Python's key advantages in microservices architecture is its simplicity and readability, making it easy for developers to quickly write, understand, and maintain code. Additionally, Python offers a wide range of frameworks and tools that support microservice development, such as Flask, FastAPI, and Django REST Framework.Python microservices offer a flexible, scalable, and efficient way to build complex applications by breaking them into smaller, manageable components. While this approach requires more attention to infrastructure and management, the advantages of faster deployment, fault tolerance, and scalability make it a popular choice for modern software development.
Who this course is for
This course is for those wanting to learn Python Microservices
Homepage

https://www.udemy.com/course/microservices-from-basics-to-advanced/

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Free Download Python Numpy Programming with Coding Exercises
Published 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 32m | Size: 312 MB
Master Numerical Computing and Data Analysis with NumPy Through Hands-On Coding

What you'll learn
How to create and manipulate NumPy arrays for efficient numerical computing.
Techniques for performing mathematical operations and statistical analysis with NumPy.
Advanced array manipulations such as reshaping, indexing, and broadcasting.
Application of NumPy in solving linear algebra problems and integrating with other data analysis tools.
Requirements
Basic knowledge of Python programming.
Understanding of fundamental mathematical concepts.
Description
Welcome to Python NumPy Programming with Coding Exercises, a comprehensive course designed to teach you the essentials of numerical computing using the NumPy library. NumPy is a fundamental package for scientific computing in Python, providing support for arrays, matrices, and a wide range of mathematical functions. This course will guide you through the core functionalities of NumPy, enhancing your ability to perform efficient data manipulation and analysis.In today's data-driven world, proficiency in numerical computing is crucial for analyzing data, performing complex calculations, and building machine learning models. NumPy's powerful array operations and mathematical capabilities make it an indispensable tool for data scientists, analysts, and engineers. This course aims to equip you with practical skills and knowledge through hands-on coding exercises that reinforce learning and apply concepts to real-world problems.Throughout this course, you will cover:Introduction to NumPy and its array objects: Understand the basics of NumPy, including array creation, manipulation, and basic operations.Array operations and mathematical functions: Learn to perform arithmetic operations, statistical calculations, and algebraic manipulations with NumPy arrays.Advanced array manipulations: Explore topics such as indexing, slicing, reshaping, and broadcasting to handle complex data structures.Numerical methods and linear algebra: Apply NumPy for solving linear algebra problems, including matrix operations and decompositions.Data analysis and integration: Use NumPy for data cleaning, transformation, and integration with other libraries like pandas.Practical exercises: Apply your skills to solve real-world problems and work with datasets to reinforce learning and practice key concepts.By the end of this course, you will be proficient in using NumPy for numerical computing, enabling you to handle large datasets efficiently and perform advanced mathematical operations with ease.Instructor Introduction: Faisal Zamir is a seasoned Python developer and educator with over 7 years of experience in teaching and working with Python libraries. Faisal's expertise in numerical computing and his clear, practical teaching approach will guide you through the intricacies of NumPy, ensuring you gain valuable skills and insights.Certificate at the End of Course: Upon successful completion of the course, you will receive a certificate that validates your skills in Python NumPy programming, enhancing your professional profile.
Who this course is for
Data scientists and analysts seeking to enhance their skills in numerical computing.
Python developers interested in mastering array operations and data manipulation.
Professionals and students aiming to apply mathematical and statistical techniques in their projects.
Homepage

https://www.udemy.com/course/python-numpy-programming-with-coding-exercises/

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Free Download Python Programming For Beginners From Basics To Advanced
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 9.09 GB | Duration: 19h 39m
Master Python Programming: Learn Syntax, Functions, OOP, and File Handling for Real-World Applications

What you'll learn
Understand Python syntax, variables, and data types to write basic programs
Implement control structures like loops and conditional statements
Build and utilize functions, including lambda functions, in Python
Apply object-oriented programming concepts like classes, inheritance, and polymorphism
Requirements
No prior programming experience required-perfect for beginners
Access to a computer with internet connection for coding exercises
Optional: Install Python and an IDE (e.g., PyCharm or Anaconda) or use Google Colab for online coding
Curiosity and a willingness to learn!
Description
Imagine this: You've always been curious about the world of technology and coding, but you've been hesitant to start. Maybe the jargon seemed overwhelming, or you felt like coding was only for those with an engineering background. But what if I told you that you could become proficient in Python, one of the most powerful and versatile programming languages in the world, without any prior experience?Now picture yourself, a few weeks from now, confidently writing your first Python program, automating tasks, analyzing data, or even building simple applications. You're the hero in this story-taking control of your learning journey, conquering new challenges, and equipping yourself with one of the most in-demand skills in today's tech-driven world.This course is designed to make you the hero of your coding adventure. Whether you're looking to start a new career, solve problems with technology, or simply satisfy your curiosity, this Python course will give you the skills you need. And the best part? No prior programming experience is required. All you need is a computer, access to the internet, and the willingness to learn and explore.What Will You Learn?By the end of this course, you will be able to:Master the basics of Python programming: Learn Python syntax, how to declare variables, use data types, and write simple programs.Work with control structures: Understand how to implement if-else statements, for loops, while loops, and other conditional logic to make your programs more dynamic.Create and use functions: Understand how to define and call functions, use parameters, and explore advanced topics like lambda functions.Understand object-oriented programming (OOP): Learn how to work with classes and objects, inheritance, polymorphism, and method overriding, making your code more efficient and reusable.Handle files: Discover how to open, read, write, and close files in Python, an essential skill for many real-world applications.Solve real-world problems: Use Python to automate repetitive tasks, manipulate data, and develop practical projects that you can apply in your personal or professional life.Why Python?Python is a high-level, versatile programming language known for its simplicity and readability, making it the perfect choice for beginners. It's also a favorite among developers, data scientists, and engineers due to its vast libraries and strong community support. Python powers everything from web development to data analysis, machine learning, and automation. So, whether you're aiming for a career in tech, looking to automate processes at work, or just want to explore programming for fun, Python is a great starting point.Who Is This Course For?This course is tailored for absolute beginners. You don't need any previous coding experience. It's ideal for:Students who want to develop coding skills for their studies or future careers.Professionals looking to upskill or transition into tech-related roles.Hobbyists or self-learners curious about programming and eager to solve problems using Python.Anyone who wants to learn how to automate tasks, analyze data, or develop web-based applications.What Tools Will You Use?In this course, you'll get hands-on experience using Python through:Google Colab: An easy-to-use, browser-based platform for writing and running Python code without installing anything on your computer.PyCharm or Anaconda: For those who prefer to set up a local Python environment, we'll walk you through the installation process and show you how to run Python code on your own machine.Jupyter Notebooks: For data analysis and visualization, a powerful tool commonly used by data scientists.Learning ApproachOur learning approach is centered around hands-on practice. Every lesson is followed by practical examples, quizzes, and coding challenges to help you reinforce what you've learned. As you progress through the course, you'll work on real-world projects that solidify your understanding and give you a portfolio of skills to showcase.Whether you're taking your first step into the world of programming or building on previous knowledge, this course will guide you through the essentials of Python in an easy-to-follow, structured way. The journey may be challenging at times, but with persistence and dedication, you'll find yourself mastering Python and unlocking new opportunities.Start Your Python JourneyYou are the hero of your own learning story. Don't let doubts or fear hold you back. Start today, and soon, you'll be navigating Python with confidence, solving problems, and perhaps even discovering a passion for coding you never knew you had.Are you ready to begin? Let's get started!
Overview
Section 1: Introduction to Python
Lecture 1 Get to Know Your Instructor
Lecture 2 What is Python? - Python Programming Language Explained
Lecture 3 Use of Python
Lecture 4 Python Code Execution
Lecture 5 Features of Python
Lecture 6 Queries Regarding Basics of Python
Section 2: Basic Building Blocks of Python
Lecture 7 Python Keywords and List of Keywords
Lecture 8 Indentation and Comments, Identifiers, Variables in Python
Lecture 9 Query Regarding Study Materials of Python
Section 3: Hands on Python Activity
Lecture 10 Using Print Statement in Python
Lecture 11 Issues Regarding PyCharm Installation
Lecture 12 Query Regarding Print Statement in Python
Lecture 13 How to Run Google Colaboratory
Lecture 14 More Queries Regarding Print Statement in Python
Lecture 15 Queries Regarding Anaconda Installation
Section 4: Using Variable in Python
Lecture 16 How to Store Value in Variable in Python
Lecture 17 Giving the Name of A Variable as A String
Lecture 18 What Double Quotes Around a Variable Do
Lecture 19 Queries Regarding Using Double Quotes Around a Variable
Lecture 20 Problem with Kernel/Connecting with Server
Lecture 21 Fixing the NameError in Jupyter Notebook
Lecture 22 Reviewing Some Activities Regarding Variable in Python
Section 5: Quick Overview on Basics of Python
Lecture 23 Uses of Python
Lecture 24 Features of Python
Lecture 25 Keywords, List of Keywords and Comments
Lecture 26 Python Identifiers and Variables
Lecture 27 Data Types in Python
Section 6: Working with Lists in Python
Lecture 28 How Python List Works
Lecture 29 How to Order Lists in Python
Lecture 30 List Slicing in Python
Lecture 31 Queries Regarding Python Lists
Lecture 32 Solving an Undefined Variable NameError in Python
Lecture 33 Fixing NameError Name is Not Defined
Section 7: Essential Python List Functions and Troubleshooting
Lecture 34 Using Python max() Function
Lecture 35 Fixing Unterminated String Literal in Python
Lecture 36 Issues Regarding Python Installation
Lecture 37 Issues Regarding Function of List
Section 8: Understanding and Troubleshooting Python Tuples
Lecture 38 What is Tuple?
Lecture 39 How do Tuples Work in Python
Lecture 40 Queries Regarding Python Tuple
Lecture 41 Issues Regarding Python Tuple
Section 9: Introduction to Python Data Types and Structures
Lecture 42 What You Have Learned So Far
Lecture 43 Different Python Datatypes
Lecture 44 Quick Overview on Python Tuple
Lecture 45 Introduction to Strings in Python
Section 10: Sets in Python : Everything You Need to Know About It
Lecture 46 What Are Python Sets
Lecture 47 Printing Set Variable
Lecture 48 How to Print with Example Syntax Command
Lecture 49 Understanding Google Colab Text color
Lecture 50 Queries Regarding Sets in Python
Lecture 51 Evaluating Assessments
Section 11: Mastering Python Dictionaries and Booleans
Lecture 52 Dictionary In Python Explained
Lecture 53 Creating Dictionary in Python
Lecture 54 Python Boolean Explained
Section 12: Operators in Python - Everything You Need to Know
Lecture 55 Introduction to Python Operators
Lecture 56 Using Addition, Subtraction, Multiplication, Division and Modulus Operators
Lecture 57 Using Comparison Operators
Lecture 58 Logical, Membership and Identity Operators
Lecture 59 Using Identity Operators in Python
Lecture 60 Queries Regarding Python Operators
Section 13: Getting Started with Conditional Statements in Python
Lecture 61 Introduction to Conditional Statements in Python
Lecture 62 Get to Know Your Instructor
Lecture 63 Decision Making Statements Explained
Lecture 64 Python If Statement Explained
Lecture 65 If...Elif....Else Statement in Python
Lecture 66 Assignments on Conditional Statements in Python
Section 14: Hands on Activity on Conditional Statements
Lecture 67 Using If Statement in Python
Lecture 68 Using If Else Statement in Python
Lecture 69 Using If...Elif...Else Statement in Python
Lecture 70 Checking If True or False Using Conditional Statement in Python
Lecture 71 Queries Regarding Checking If True or False Using Conditional Statement
Lecture 72 Comparing Two Numbers
Lecture 73 Queries Regarding Conditional Statements
Section 15: Handling User Input and Integrating Online Tools in Python
Lecture 74 Taking Integer Input in Python
Lecture 75 Using Authorization Flow in Python
Lecture 76 Using Another Online Tool to Run Python Code
Lecture 77 Queries Regarding Python input() Function
Section 16: Mastering Python Loops: For Loops and Beyond
Lecture 78 Types of Loops in Python
Lecture 79 Python For Loops Explained
Lecture 80 Calculating Table with Loop
Lecture 81 Flow Chart For Loop
Lecture 82 Queries Regarding For Loop
Section 17: Understanding and Using Python Loops and Break Statements
Lecture 83 Python While Loop Explained
Lecture 84 Python Break Statement with Flowchart
Lecture 85 Working of Break with For and While Loop
Section 18: Hands on Activity on Python Loops
Lecture 86 Printing Digits using For Loop
Lecture 87 Sum of Digits of a Number in Python
Lecture 88 Python Looping Through a Range
Lecture 89 Queries Regarding Looping Through a Range
Lecture 90 Using a Break Statement with For Loops
Lecture 91 Using If-Else Statements and While Loops in Python
Lecture 92 Queries Regarding Accessing the Resources
Section 19: Introduction to Python Functions: Basics and Syntax
Lecture 93 What You Have Learned So Far
Lecture 94 Making a "sub" Function
Lecture 95 What Is Function?
Lecture 96 Queries Regarding Basics of Function
Lecture 97 Creating a Function Syntax
Section 20: Defining and Calling a Function
Lecture 98 Defining Any Name in Python
Lecture 99 Defining Multiplication Function and Calling Sum Function in Print Statement
Lecture 100 Queries Regarding Defining Sum Function
Lecture 101 Creating Function Without Return Statement and Defining Square Number
Lecture 102 Evaluating Assessments
Section 21: Working with Parameters in Python Functions: Definition, Issues, and Assessment
Lecture 103 Using Parameters in Sum Function
Lecture 104 Defining Sum Function Using Parameters
Lecture 105 Issues Regarding Defining Sum Function Using Parameters
Lecture 106 Defining Name as Function and Printing The Hello Statement
Lecture 107 Queries Regarding Using Parameters in Function
Lecture 108 Evaluating Assessments
Section 22: Creating and Using Functions with Arguments in Python
Lecture 109 What You Have Learned So Far
Lecture 110 Creating a Function With Arguments
Lecture 111 Example on Creating a Function With Arguments
Section 23: Exploring Python Lambda Functions: Basics and Practical Applications
Lecture 112 What is Lambda Function in Python
Lecture 113 Adding 10 to Argument A and Returning The Result
Lecture 114 Queries Regarding Lambda Function
Lecture 115 Program to Filter Out Only The Even Items From The List
Lecture 116 Program to Filter Out Only The Odd Items From The List
Lecture 117 Program to Filter Out Numbers Which are Greater Than 60 Using Lambda Function
Section 24: Using Python Map, Local & Global Variables: Concepts and Examples
Lecture 118 Program to Double Each Item in a List Using Map
Lecture 119 Program to Add 10 to All The Values Using Map
Lecture 120 What is a Local and Global Variable in Python?
Lecture 121 Using Global Variable and Local Variable With the Same Name in Python
Lecture 122 What are The Applications of Global and Local Variables?
Lecture 123 Queries Regarding Global and Local Variables
Lecture 124 Query Regarding Filtering Even Numbers Using Lambda Function
Section 25: Introduction to Object-Oriented Programming in Python: Classes and Objects
Lecture 125 What You Have Learned So Far
Lecture 126 What is Object Oriented Programming
Lecture 127 Class in Python Explained
Lecture 128 Syntax and Object in Python
Lecture 129 Program to Demonstrate Class and Object Concept
Section 26: Troubleshooting Functions and Attributes in Python: Common Issues and Solutions
Lecture 130 Why a Function Could Not Be Executed in Python
Lecture 131 Why is Dot Operator Used in Python
Lecture 132 Can We Have More Than One Object For The Same Class in Python
Lecture 133 Query Regarding Display Function in Python
Lecture 134 Fixing AttributeError in Python
Section 27: Understanding and Implementing Constructors in Python
Lecture 135 What is A Constructor in Python
Lecture 136 Creating The Constructor in Python
Lecture 137 Counting The Number of Objects with Non Parameterized Constructor
Lecture 138 Fixing Invalid Syntax in Python SyntaxError
Lecture 139 Fixing Issues Regarding Counting The Number of Objects
Lecture 140 Short Recap on Object Oriented Programming and Python Constructor
Lecture 141 Query on Extracting The Object Values Using Map
Section 28: Exploring Inheritance in Python: Types and Examples
Lecture 142 Recap on What You Have Learned So Far
Lecture 143 What is an inheritance in Python
Lecture 144 Types of Inheritance in Python
Lecture 145 Single Inheritance in Python Explained
Lecture 146 Multilevel Inheritance in Python with Example
Lecture 147 Multilevel Inheritance in Python Explained
Section 29: Mastering Multiple Inheritance in Python: Concepts and Examples
Lecture 148 Multiple Inheritance in Python Explained
Lecture 149 Example of Multiple Inheritance in Python
Lecture 150 Queries Regarding Multiple Inheritance
Lecture 151 Fixing Errors Regarding Multiple Inheritance
Lecture 152 How to Use an Input() Function Within a Class in Python
Section 30: Understanding and Implementing Method Overriding in Python
Lecture 153 Method Overriding in Python Explained
Lecture 154 Real Life Example Method Overriding
Lecture 155 Query on Method Overriding
Lecture 156 Use of Python super() Function
Section 31: Overview on What You Have Learned So Far
Lecture 157 Problems Regarding Practice Codes
Lecture 158 Basics Of Python
Lecture 159 Class and Object in Python
Lecture 160 Creating The Constructor in Python
Lecture 161 Types of Inheritance in Python
Lecture 162 Method Overriding Explained
Lecture 163 Queries on Object Oriented Programming
Lecture 164 Additional Queries on Object Oriented Programming
Section 32: Understanding Polymorphism in Python: Concepts and Examples
Lecture 165 What is Polymorphism in Python
Lecture 166 Polymorphism in len() Function in Python
Section 33: File Handling in Python: Functions, Queries, and Applications
Lecture 167 Python File Open Function
Lecture 168 How to Open and Close a File in Python
Lecture 169 Queries on Python Open File Function
Lecture 170 Why Visual Studio Code is Used
Lecture 171 Queries Regarding Commands Used for File Handling in Python
Lecture 172 Can Python be Used for Data Analysis?
Lecture 173 What Is Python Used For?
This course is designed for beginners with no prior coding experience who want to learn Python from scratch. It's also ideal for students, professionals, and hobbyists interested in developing their programming skills for data analysis, automation, web development, or any field that requires coding knowledge. Additionally, anyone looking to transition into tech or enhance their problem-solving and logical thinking abilities will find this course valuable.
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Free Download Python Programming Language For Complete Beginners
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.01 GB | Duration: 9h 13m
On completion of this course you would be able to tackle programs in python

What you'll learn
The students after learning this python course would be able to get a basic understanding of what python is and will be able to solve problems regarding python
This course covers algorithms, syntax, comments, loops, while loop, for loop, if statements elif statements, data types, variables, lists, tuples, functions
Then it will also cover library modules , operator in python, strings, slicing operations
They will get 20 python projects and 2 mini projects with their solutions
Requirements
No programming knowledge required
Description
This 25-video course is designed to introduce absolute beginners to the fundamentals of Python programming. Whether you are new to coding or looking to sharpen your skills in one of the most versatile and popular programming languages, this course will help you build a strong foundation. Python's simple syntax and readability make it an ideal starting point for anyone stepping into the world of programming.Throughout the course, you will cover a wide range of topics, including basic data types, control structures, functions, and modules. You'll learn how to manipulate strings, lists while understanding the importance of logic and flow in programming. As the course progresses, you will also gain practical experience by building real-world applications.Each day's session includes hands-on coding exercises and mini-projects, ensuring that you can immediately apply the concepts you learn. By the end of the course, you will be able to write clean, efficient, and well-structured Python code, and have the confidence to continue exploring advanced topics or transition into other programming languages.No prior programming experience is required, only a willingness to learn and explore. Join us to kickstart your journey in Python and discover the endless possibilities of coding! Lets see you in the course
Overview
Section 1: Intro and Basics
Lecture 1 Intro
Lecture 2 problems, algorithms and features
Section 2: starting of with python
Lecture 3 variables and data-types
Lecture 4 indentation, comments and input operations
Lecture 5 operators in python
Lecture 6 programs
Section 3: if conditions and loops in python
Lecture 7 if condition
Lecture 8 elif correction
Lecture 9 nested if
Lecture 10 while loop
Lecture 11 for loop(1)
Lecture 12 for loop(2)
Lecture 13 for loop(3)
Lecture 14 break statement in python
Section 4: Tuples and Lists
Lecture 15 lists(1)
Lecture 16 lists(2)
Lecture 17 lists(3)
Lecture 18 lists methods(4)
Lecture 19 tuples(1)
Lecture 20 operations of tuples(2)
Section 5: funtions and modules
Lecture 21 functions(1)
Lecture 22 functions(2)
Lecture 23 global and local variables
Lecture 24 calculator program in python
Lecture 25 Strings in python
Lecture 26 modules in python
11th , 12th, 1st/2nd year BE, Btech, BSC, BCA student Or anyone who wants to explore python programming language
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Homepage

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Free Download Python Programming Mastery From Beginner to Pro
Published 10/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 8m | Size: 621 MB
Python Pro: Master Programming and Problem-Solving Skills

What you'll learn
Understand and apply fundamental Python concepts, including variables, data types, operators, and control structures.
Gain the ability to solve real-world problems by writing efficient, reusable Python code.
Learn to leverage Python's standard libraries and external packages to streamline data manipulation, web development, and automation tasks.
pply Python skills in hands-on projects, such as building applications, automating tasks, and analyzing data, to reinforce learning and demonstrate proficiency.
Requirements
No prior experience is needed
Description
Unlock the Power of Python - From Beginner to ProWelcome to Python Programming Mastery: From Beginner to Pro! This course is designed to take you on a comprehensive journey from Python basics to advanced programming techniques. Whether you're starting fresh or looking to sharpen your skills, this course equips you with the tools, techniques, and problem-solving abilities needed to excel in Python programming.What You'll Learn:Foundational Python Concepts: Master variables, data types, control structures, and functions.Advanced Techniques: Dive into object-oriented programming, modules, and libraries to elevate your skills.Real-World Applications: Tackle hands-on projects to solidify your understanding, including data analysis, web scraping, and automation.Problem-Solving Essentials: Develop critical problem-solving skills and learn to write clean, efficient code.By the end of this course, you'll not only understand Python's core principles but also have the confidence to apply them in diverse fields like data science, web development, and automation. Our engaging lessons, comprehensive exercises, and real-world challenges ensure you're prepared to confidently build applications, automate workflows, analyze data, develop complex algorithms, and even launch your own innovative projects. Join us to become a Python Pro, equipped with highly marketable, in-demand skills for today's tech-driven world! So what are you waiting for?
Who this course is for
Beginner Python Developers
Homepage

https://www.udemy.com/course/python-programming-mastery-from-beginner-to-pro/

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Free Download QGIS Quickstart by Jack Hansen
Published 10/2024
Created by Jack Hansen
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 65 Lectures ( 4h 37m ) | Size: 3.35 GB

A beginner's guide to quickly get you started with QGIS!
What you'll learn
Basic map creation
Data management
Common geoprocessing tasks
Layer styling and cartography
Advanced mapping techniques
Plugins and extensions
Spatial analysis
Web mapping
Raster operations
Requirements
No QGIS experience necessary!
Description
Don't waste your time watching courses that take 12 hours to teach you what this course can cover in just a fraction of that time! My goal is to equip you with essential skills and tools that will empower you to navigate QGIS independently. Once you grasp these key concepts, you'll find you won't need my assistance for much else. QGIS is designed to be user-friendly, especially once you familiarize yourself with its functionalities. In this course, we begin with the basics, focusing on essential map navigation techniques and how to import various file types seamlessly. As you build your foundational knowledge, we'll gradually transition into more advanced topics, including the use of plugins and extensions that enhance your capabilities. You'll also dive into advanced spatial analysis techniques and raster analysis, both of which are crucial for making informed decisions based on geographical data. By the end of this course, you'll be equipped with the tools and confidence to be a proficient QGIS user, ready to tackle your projects with ease. This course is designed to maximize your learning in a minimal amount of time, so let's get started on this exciting journey into the world of QGIS!Dont wait. Get started on your QGIS Quickstart journey NOW!
Who this course is for
All geospatial professionals and anyone else thats interested.
Homepage

https://www.udemy.com/course/qgis-quickstart/

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Free Download QRadar - Learn Cybersecurity Fast
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 120.90 MB | Duration: 0h 45m
QRadar For DUMMIES

What you'll learn
Learning QRadar basics.
Learning cybersecurity stuff.
Enhancing your informatics education.
Getting tips to study better.
Requirements
Computer and speakers.
Description
Learning QRadar but would like to get and introduction first? You are learning about cybersecurity and would like to understand what QRadar is about? Then, THIS IS THE COURSE FOR YOU! Learning is a never ending process and cybersecurity is a big topic for sure. Thus, it will be necessary that you get your starting point as soon as you can because time is running and other people are already doing it while you read this very message. But no worries, we are here to cover you. Now you will be able to learn about QRadar and about the many things that it implies. Cybersecurity is likely to be a very required topic by many enterprises that work with technology and if you are the guy who will eventually have this knowledge, you can be sure that you will be seen as a good candidate in more than one job because not everyone out there understands cybersecurity and QRadar. The more you learn, the better for you, it is going to be nice to give the step today so that you get your learning process started and that is going to be something useful to do. Worth saying that you can learn about QRadar in terms of terminology which we will tell you about in this course. You can expect lots of information and tips to learn at the end of the course so that you really are pretty prepared for what comes next in your career. See you in the other side!
Overview
Section 1: Intro
Lecture 1 Intro
Lecture 2 Indeed
Lecture 3 Useful
Lecture 4 Learning
Lecture 5 Enhance
Lecture 6 Stuff
Lecture 7 Great
Lecture 8 Remember
Lecture 9 Interesting
Lecture 10 Ideas
Lecture 11 Technically
Lecture 12 Tips
Lecture 13 More
Lecture 14 Unique
Lecture 15 Powerful
Lecture 16 Almost
Lecture 17 Also
Lecture 18 End
Anybody who wants to learn QRadar.
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Free Download Qigong Energy Cultivation y Kung Fu Kendra
Published 10/2024
Created by Kung Fu Kendra
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 8 Lectures ( 2h 7m ) | Size: 2.5 GB

Learn and Practice Qiqong.
What you'll learn
Qigong History and Foundations
Breath and Energy Awareness
Foundational Stances and Movements
The Eight Pieces of Brocade
Completing the Eight Pieces of Brocade
Shaolin Self-Massage Techniques
Advanced Qigong Practices
Creating Your Daily Qigong Routine
Requirements
No Previous Experience Required
Description
Do you wish you could stop struggling with feeling stressed, drained and disconnected from your body's natural flow of energy? Wishing you had more vitality, motivation and clear mind to enjoy your life to the fullest?I'm Kendra Mahon known as Kung Fu Kendra and I'm a black black belt, kung fu martial artist and bestselling author with over twenty years experience in meditation, martial arts and Qigong coaching and I'm here to introduce you to a life-changing practice that has transformed the health and vitality of countless individuals for over a thousand years. I've taken what I've learned as a martial arts master and turned it into a step by step solution, a blueprint that you can follow to have success. And with my twenty plus years of experience in martial arts training and with my knowledge of ancient shaolin techniques and with my experience working with celebrities and top tech executives as well as everyday people you are in good hands. Here's what's in the program:Module 1 In the first module I will teach you:The history and philosophy of Shaolin QigongHow Qigong boosts vitality, health, and spiritual energyThe foundational principles of energy cultivationPreparing your mind and body for Qigong practice.Module 2 Breath and Energy Awareness. In this module, we'll focus on:The importance of proper breathing in QigongTechniques for abdominal breathing and reverse breathingCultivating awareness of your body's energy (Qi)Simple standing meditation to feel your Qi.Module 3 Foundational Stances and Movements. The Horse Stance and its variationsBasic Qigong arm movements and their benefitsCoordinating breath with movementThe "Ball of Energy" exercise for Qi circulation.Module 4 The Eight Pieces of Brocade (Baduanjin )In this module, we'll learn:The history and benefits of the Eight Pieces of BrocadeDetailed instruction for the first four movementsHow these exercises boost organ health and overall vitalityIntegrating breath and intention into each movement.Module 5 Completing the Eight Pieces of Brocade. Building on the previous module, we'll cover:The remaining four movements of the BaduanjinHow each movement targets specific health benefitsTips for deepening your practice and feeling the Qi flowA full run-through of all eight movements.Module 6 Shaolin Self-Massage Techniques In this module, we'll explore:Traditional Shaolin self-massage methods for energy cultivationTechniques for stimulating acupressure pointsFacial and scalp massage for mental clarity and stress reliefFull-body energy tapping to invigorate your Qi.Module 7 Advanced Qigong Practices.The Small Heavenly Circuit meditation for advanced energy circulationStanding post exercises (Zhan Zhuang) for deep energy cultivationTechniques for directing Qi to specific areas of the bodyIntegrating visualization with physical practice.Module 8 Creating Your Daily Qigong Routine In our final module, we'll coveresigning a personalized daily Qigong practiceTips for maintaining consistency and overcoming obstaclesHow to progress and deepen your practice over timeIntegrating Qigong principles into your daily life for ongoing vitality and spiritual growth.This program is amazing because it takes you on a journey from beginner to advanced Qigong practitioner, teaching youThe foundational principles of energy cultivationPowerful breathing techniques to instantly calm your mind and energize your bodySimple yet effective movements to stimulate your body's natural healing abilitiesAdvanced practices for deep energy circulation and spiritual growth.
Who this course is for
This Course is for Everyone
Homepage

https://www.udemy.com/course/qigong-energy-cultivation/

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Free Download Qradar In A Nutshell A Course For Everyone
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 123.06 MB | Duration: 0h 47m
A Course To Get STARTED

What you'll learn
Learning QRadar basics.
Learning informatics stuff.
Enhancing your QRadar education.
Getting tips to study better.
Requirements
Computer and speakers.
Description
Are you learning QRadar and you want to give the first steps? You are into learning about QRadar but feel like you are still a beginner? Then, THIS IS THE COURSE FOR YOU! If your idea is to improve in the world of QRadar then you can try improving as much as possible with this course. The more you learn, the better you get. It is going to be a matter of enhancing your skills because now you do have the internet, no excuses, you can learn from your very smartphone. Also, the fact is that you are going to receive some education in the world of infomratics with QRadar related ideas and topics. What can you expect? You will see lots of information and important ideas that could be necessary to remember when you are learning about QRadar. Consider you are going to be getting more and more information that is going to be part of the NoSQL QRadar set since at the end of the day, learning is filled of lots of ideas that you should not miss in general.Having said that, you are now ready to get started in the QRadar road. It is good that you know that you are going to be needing to let your skills go as further as you can because that is going to be part of the required things to do.Other than that, you are alreeady done, if you want to get an introduction, you are some clicks away from doing that. See you in the other side of the learning process!
Overview
Section 1: Intro
Lecture 1 Intro
Lecture 2 Ready
Lecture 3 Also
Lecture 4 Cenrtered
Lecture 5 Working
Lecture 6 Enjoy
Lecture 7 Good
Lecture 8 Train
Lecture 9 Remember
Lecture 10 More
Lecture 11 Advance
Lecture 12 Real
Lecture 13 Needed
Lecture 14 Power
Lecture 15 Useful
Lecture 16 Imporve
Lecture 17 Learning
Lecture 18 End
Anybody who wants to learn QRadar.
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Homepage

https://www.udemy.com/course/qradar-in-a-nutshell-a-course-for-everyone/

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Free Download Quality Management Toolkit
Published 10/2024
Created by Dr. Kamran Moosa
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 Lectures ( 7h 5m ) | Size: 2.85 GB

25 Essential Quality and Lean Management Tools Every Professional Should Know
What you'll learn
Learn strategic tools for aligning organizational goals with quality initiatives.
Prepare yourself to Implement Lean and quality management tools for continuous improvement.
Explore customer needs while conducting effective benchmarking to design products or services.
Identify important data-driven problem-solving techniques and quality improvement tools.
Measure and monitor processes to ensure consistent performance.
Build insight into most common Lean management techniques to eliminate waste and optimize efficiency.
Explore global frameworks and standards to drive organizational excellence.
Requirements
Anyone interested or working in the field of Quality or Lean Management
Description
Expand Your Knowledge with Essential Quality and Lean Management ToolsAre you ready to equip yourself with the most essential tools in quality and lean management? Whether you're just beginning or seeking to sharpen your expertise, this Quality Management Toolkit course is designed for professionals who want to strengthen their foundation with 25 Essential Quality and Lean Management Tools Every Professional Should Know. This course offers a strategic understanding of these tools, giving you the insights needed to implement real improvements in your organization. It is ideal for anyone eager to enhance their quality management skills and make a lasting impact.The course delivers a broad overview of essential tools and techniques in quality management and Lean methodologies, categorized into seven key areas crucial to achieving operational excellence. From strategic planning to statistical process measurement, these tools will help professionals-whether you're a Quality Manager, Lean professional, auditor, or consultant-tackle challenges and lead initiatives that elevate both processes and customer satisfaction. This is your opportunity to gain actionable insights, broaden your expertise, and start making a difference. Enroll today and build your foundation for success!Key Categories Covered:Strategic Planning and Management:Learn strategic frameworks like Balanced Scorecard (BSC), Hoshin Kanri, and SWOT Analysis to effectively plan and manage organizational strategies.Continuous Improvement:Explore proven methodologies such as Kaizen, Quality Circles, and Gemba Walks that foster ongoing process improvements and better performance.Customer Focus and Benchmarkingiscover tools like Quality Function Deployment (QFD), Kano Model, and Benchmarking to prioritize customer satisfaction and maintain a competitive edge.Problem-Solving and Analysis:Master techniques such as Six Sigma, A3 Problem Solving, Theory of Constraints (ToC), and Poka Yoke to address inefficiencies and resolve operational issues.Statistical Process Monitoring & Measurement:Understand and implement tools like SPC Charts, GRR, Cost of Poor Quality (COPQ), and Overall Equipment Effectiveness (OEE) to monitor and enhance process performance.Lean Managementive into Lean practices like Value Stream Mapping (VSM), Kanban, Just-In-Time (JIT), and 5S to streamline operations and reduce waste.Business Excellence Models and ISO Management Standards:Learn how to apply international frameworks like Baldrige, EFQM, and ISO standards to promote excellence and ensure compliance.
Who this course is for
This course is designed for quality professionals, managers, consultants, auditors, and business leaders across industries. Whether you're starting fresh or seeking to refresh and expand your knowledge, this course will provide valuable insights and tools for implementing quality initiatives in any organization.
Homepage

https://www.udemy.com/course/quality-management-toolbox/

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Free Download Quantitative Analysis of Data Using SPSS V29
Published 10/2024
Created by Alain Tannous
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 21 Lectures ( 4h 19m ) | Size: 1.93 GB

Quantitative Analysis, SPSS Software, Tests and Conclusions
What you'll learn
Explain the six SPSS windows and their specific uses.
Calculate the mean, sum, standard deviation, variance, and more.
Examine relationships using Scatter Plot and Scatter Plot Matrices.
Test for Normality and Homoscedasticity.
Explain numerical measures such as Central Location, Dispersion, Skewness, Kurtosis and Linearity.
Identify and differentiate between the different forms of outcomes.
Differentiate between the statistical types I and II errors.
Construct a multiple regression model, identify its elements and list its assumptions.
Learn to use the Ordinary Least Squares (OLS) regression method to estimate the coefficients.
Define the Standard Error of Estimates (SEE), explain its role in regression model and understand its visual representation.
Relate SEE to R-squared and the overall performance of the regression model.
Define ANOVA, explain its assumptions and significance in regression analysis, set its hypotheses, conduct ANOVA analysis using SPSS and explain its outcomes.
Formulate the null and alternative hypotheses.
Conduct a statistical T-test to assess and interpret the significance of the coefficients.
Define autocorrelation, identify its impact on regression models and test for autocorrelation using Durbin-Watson Test.
Explain the importance of forecasting time series data and perform a forecast seasonal time series data using SPSS V29.
Define MANOVA, explain its assumptions and significance in regression analysis, set its hypotheses, conduct MANOVA test using SPSS and explain its outcomes.
Generate different tests related to MANOVA such as: Box's M Test, Hotelling's T Squared, Pillai's Trace Test and Wilk's Lambda Test.
Formulate and test the hypotheses of all MANOVA tests using SPSS.
Compose and test the hypotheses for Levene's Test of homogeneity of variances.
Define Discriminant analysis and identify its variables, assumptions and hypotheses.
Test for Multivariate Normality, Equality of Covariances and Vectors of Means.
Perform a stepwise discriminant analysis and analyze its outcomes using the cross-validation method.
Define logistic regression, identify its variables and assumptions, compose its hypotheses, perform a stepwise logistic regression test and analyze its outputs.
Define the Principal Component Analysis (PCA), identify its key variables and assumptions, and conduct a PCA analysis following a detailed procedure on SPSS.
Define Factor Analysis (FA), identify its assumptions, variables and hypotheses, and conduct all FA tests and analyze their outcomes.
Define Cluster Analysis, identify its assumptions, variables and hypotheses, and conduct all FA tests and analyze their outcomes.
Apply all tests using practical exercises on SPSS
Requirements
No prerequisites are required. You will learn all steps in this course.
Description
This course offers a detailed exploration of quantitative data analysis using SPSS V29, a powerful software tool widely used in research fields such as social sciences, business, healthcare, and education. Designed for both beginners and intermediate users, the course covers essential statistical techniques and guides learners through the process of managing, analyzing, and interpreting quantitative data. Over 4 hours and 20 minutes of recorded lectures, accompanied by PDF notes for each session, will introduce you to core concepts in data analysis, such asata entry, management, and cleaning techniques using SPSS V29Descriptive statistics, including measures of central tendency and variabilityInferential statistics such as t-tests, ANOVA, regression analysis, and chi-square testsMultivariate analysis techniques, including factor analysis, discriminant analysis, and cluster analysisReporting and interpreting statistical outputs effectivelyUsing visual tools like graphs and charts for data presentationThe course also includes SPSS data files for hands-on practice, ensuring that students gain practical experience working with real datasets.Additionally, a quiz at the end of each lesson allows students to assess their understanding and apply the skills learned. By the end of this course, participants will be able to effectively use SPSS V29 to perform complex statistical analyses, create meaningful data visualizations, and report results professionally and clearly, equipping them with the tools needed for academic research or professional projects.
Who this course is for
Graduate and Postgraduate students who are engaged in writing their thesis or dissertation which is based on a quantitative analysis of data.
Beginner researchers who require a tool to analyze their findings.
Homepage

https://www.udemy.com/course/quantitative-analysis-of-data-using-spss-v29/

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Free Download Quantization for GenAI Models by Start-Tech Academy
Published 10/2024
Created by Start-Tech Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 34m ) | Size: 807 MB

Unlock the power of model optimization! Learn how to apply quantization and make your GenAI models efficient with Python
What you'll learn
Understand model optimization techniques: Pruning, Distillation, and Quantization
Learn the basics of data types like FP32, FP16, BFloat16, and INT8
Master downcasting from FP32 to BF16 and FP32 to INT8
Learn the difference between symmetric and asymmetric quantization
Implement quantization techniques in Python with real examples
Apply quantization to make models more efficient and deployment-ready
Gain practical skills to optimize models for edge devices and resource-constrained environments
Requirements
Basic Python knowledge is recommended, but no prior AI experience is required.
Description
If you are a developer, data scientist, or machine learning enthusiast who wants to optimize and deploy efficient AI models, this course is for you. Do you want to make your models faster and more resource-efficient while maintaining performance? Are you looking to learn how to apply quantization techniques for better model deployment? This course will teach you how to implement practical quantization techniques, making your models lean and deployable on edge devices.In this course, you will:Learn the core concepts of Quantization, Pruning, and Distillation.Understand different data types like FP32, FP16, BFloat16, and INT8.Explore how to convert FP32 to BF16 and INT8 for efficient model compression.Implement symmetric and asymmetric quantization in Python with real-world applications.Understand how to downcast model parameters from FP32 to INT8 for deployment.Gain hands-on experience with Python-based quantization, making your models suitable for mobile and IoT devices.Why learn quantization? Quantization allows you to reduce the size and computational load of models, making them suitable for resource-constrained devices like smartphones, IoT devices, and embedded systems. By mastering quantization, you can ensure your models are faster, more energy-efficient, and easier to deploy while maintaining accuracy.Throughout the course, you'll learn to implement quantization techniques and optimize your models for real-world applications. This course provides the perfect balance of theory and practical application for making machine learning models more efficient.By the end of the course, you'll have a deep understanding of quantization, and the ability to optimize and deploy efficient models on edge devices. Ready to optimize your AI models for efficiency and performance? Enroll now and start your journey!
Who this course is for
Beginners in machine learning looking to learn practical model optimization techniques like quantization
AI professionals and students wanting to optimize models for deployment on resource-constrained devices
Homepage

https://www.udemy.com/course/quantization/

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Free Download Quantum Cryptography and the Future of Cybersecurity
Last updated 10/2024
With Jonathan Reichental
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 31m 56s | Size: 101 MB

Quantum cryptography is poised to shake up the world of information security. This course explains what it is, how it works, and the challenges and opportunities that lie ahead.
Course details
The frequency and severity of hacking and other attacks on our information systems are increasing. Despite remarkable progress in cybersecurity innovation, too many vulnerabilities continue to exist, and the threats are increasingly sophisticated. Quantum cryptography may offer some optimism in the long term. By leveraging the fundamentals of quantum mechanics, this set of emerging technologies allows information to be protected in novel new ways. Consequently, it's poised to shake up the world of information security. In this course, Jonathan Reichental lays out what quantum cryptography is, as well as the journey ahead to operationally realize quantum-based encrypted communications.
Homepage

https://www.linkedin.com/learning/quantum-cryptography-and-the-future-of-cybersecurity

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