All mitsumi'1s Applications !! (updated daily) - Страница 4429

mitsumi1 · 20.07.2021, 08:47

What you'll learn:
Students can learn computer communication and networking fundamentals through simulation software.

Requirements
Basic understanding of concepts in the field of computer communication like switches, hubs, routers,Wireless LAN is required.

Description
The internet has become one of the most important components of our life. We browse the web, check e-mails, make VoIP phone calls, and have video conferences via computers. All of these applications are made possible by networking computers together. A system of interconnected computers and computerized peripherals is called computer network.

This course gives the detail instructions about the computer communication and networking hands on experience by configuring various devices in Cisco packet tracer.

Cisco packet tracer is an open source tool available which is easy to operate and have numerous features to configure real time environment.

The course is arranged as follows:

Introduction to Packet Tracer

Introduction to Networking Devices

Server Simulations:

1) Simulation of a network consisting of PCs connected to HTTP servers

2) Simulation of a network consisting of PCs connected to DNS servers

3) Simulation of a network consisting of PCs connected to FTP server and configuring the server for a given user id and password

4) Simulation of a network consisting of PCs connected to DHCP server and assigning IP addresses to all the devices in the network through DHCP

5) Simulation of a network consisting of PCs connected to an Email server and send email to other devices in the network

Router Simulations

6) Configuration of ROUTER through Command Line Interface.

7) Configuration of Static Routing

8) Configuration of Dynamic Routing

9) Configure a Wireless LAN

Who this course is for
Electronics/Electronics and Communication /Computer students

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/73ce6592acdbdd47b45c92492d75b337/ntz45.Learning.Computer.Communication.and.Networking.Fundamentals.rar.html

uploadgig_com:
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nitroflare_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 20.07.2021, 08:49

Learn R, Python, Machine Learning, Deep Learning, Google Colab, Real world projects with Code and step by step guidance

What you'll learn:
Why we need Data Mining & Machine Learning
What is Data Mining
What is Machine Learning
Traditional Programming Vs Machine Learning
Steps to Solve a Data Mining & Machine Learning Problem
Types of Learning in Machine learning (Supervised, Unsupervised, Reinforcement )
Classification & Clustering
Setting up the Environment for Machine Learning - R language and R studio , Python, Anaconda
Introduction to Deep Learning - Guest Lecture
Machine learning project : Car Price Prediction Project
Kaggle - Covid 19- Classification (Chest X-ray.) - Covid-19 & Pneumonia
Supervised Learning
Unsupervised Learning

Requirements
Computer with Internet connection
Python or any programming language

Description
Academy of Computing & Artificial Intelligence proudly present you the course "Data Engineering with Python". It all started when the expert team of Academy of Computing & Artificial Intelligence (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2021.

At the end of the Course you will be able to start your career in Data Mining & Machine Learning.

1) Introduction to Machine Learning - [A -Z] Comprehensive Training with Step by step guidance

2) Setting up the Environment for Machine Learning - Step by step guidance [R Programming & Python]

3) Supervised Learning - (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines (SVM), Random Forest)

4) Unsupervised Learning

5) Convolutional Neural Networks - CNN

6) Artificial Neural Networks

7) Real World Projects with Source

Course Learning Outcomes

To provide awareness of (Supervised & Unsupervised learning) coming under Machine Learning (Why we need Data Mining & Machine Learning, What is Data Mining, What is Machine Learning, Traditional Programming Vs Machine Learning, Steps to Solve a Data Mining & Machine Learning Problem, Classification , Clustering)

Describe intelligent problem-solving methods via appropriate usage of Machine Learning techniques.

To build appropriate neural models from using state-of-the-art python framework.

To setup the Environment for Machine Learning - Step by step guidance [R Programming & Python]

Convolutional Neural Networks - CNN

Resources from MIT and many famous Universities

Projects with Source

Who this course is for
Anyone who wish to start the career in Data Science & Machine Learning

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/89662f81d5938dabc8c4dface87fec44/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part1.rar.html
https://rapidgator.net/file/dc1348efc5762989569466c71798e9f4/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part2.rar.html
https://rapidgator.net/file/38117cf4c4795a095adc31040e1c2427/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part3.rar.html

uploadgig_com:
https://uploadgig.com/file/download/5144E545115b4327/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part1.rar
https://uploadgig.com/file/download/0bE72a69Bc21f746/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part2.rar
https://uploadgig.com/file/download/9a5388467599b900/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part3.rar

nitroflare_com:
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https://nitroflare.com/view/B2205A47AA47E7A/hewu4.Machine.Learning..Data.Science.Bootcamp.with.R..Python.072021.part3.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 20.07.2021, 08:50

Having a sales process is critical to a salesperson's success. But a process isn't enough if you don't follow it on each and every call. Turning your sales process into a habit that feels natural is the key. In this course, CEO and author Jeff Bloomfield helps you create a sales process that is easy to follow, keeps you on track, and helps consistently close sales. He teaches you the difference between a sales process and sales methodology and shows how to close the gap between philosophy and strategy. He then helps you define and map your sales process-from understanding your buyer to reporting results-and set the expectations for the actual conversation: what you should know, do, say, and show. Follow along and learn how to create your own winning formula to turn prospects into customers-one step at a time.

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/f79b1c4a6ac5c84892e6713ed952071d/9zyay.Managing.Your.Sales.Process.rar.html

uploadgig_com:
https://uploadgig.com/file/download/8f281f46487e7a57/9zyay.Managing.Your.Sales.Process.rar

nitroflare_com:
https://nitroflare.com/view/60EE6467DD69204/9zyay.Managing.Your.Sales.Process.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 20.07.2021, 08:52

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.20 GB | Duration: 2.4 hours

Angular is a powerful and feature-complete framework that you can use to build the best web apps. Built with TypeScript in mind, Angular takes advantage of futuristic language features such as decorators and interfaces, which make coding faster and easier.

If you want to create modern web apps with Angular, this is the course for you. In this course, Jeremy McPeak will show you how to code a complete web app with Angular, using the most current features and architectural patterns. Follow along with Jeremy and build a full-featured responsive app, with routes, asynchronous data, and authentication. So let's get started!

Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/81270b8b56649a06052b0cfd177aa0da/hm2rx.Modern.Web.Apps.With.Angular.part1.rar.html
https://rapidgator.net/file/d1eaad8b0c2bf0bf7bc1f8cd85374e80/hm2rx.Modern.Web.Apps.With.Angular.part2.rar.html

uploadgig_com:
https://uploadgig.com/file/download/a5B240609278314e/hm2rx.Modern.Web.Apps.With.Angular.part1.rar
https://uploadgig.com/file/download/a4f55bA324638522/hm2rx.Modern.Web.Apps.With.Angular.part2.rar

nitroflare_com:
https://nitroflare.com/view/D94F987F61299FD/hm2rx.Modern.Web.Apps.With.Angular.part1.rar
https://nitroflare.com/view/8F5A171FD9182BD/hm2rx.Modern.Web.Apps.With.Angular.part2.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 20.07.2021, 08:53

What you'll learn:
NextJS basics like setting up project, navigating between pages and data fetching
NextJS advanced topics like dynamic routing, image optimization, SSG and SSR
MaterialUI framework to build responsive website using custom theme, animation and carousel
ReactJS including decomposing components, context API and hooks
Next Connect package to build backend API
MongoDB and Mongoose to save and retrieve data like products, orders and users
PayPal developer api to make online payment
Deploy web applications on servers like Vercel and Netlify

Requirements
React basics like component, state and hooks

Description
Hello and Welcome to Next Amazona, a coding course to build an eCommerce website like amazon by NextJS. In this course, you will learn the essential tools and skills to design, develop and deploy a fully-function eCommerce website like amazon from scratch.

I designed this course for anyone seeking to develop a full-functional eCommerce website like amazon.

By the end of this course, you'll be able to

Design a responsive eCommerce website

Create user and SEO friendly frontend

Build a scalable backend

Connect your ECommerce website to payment gateways

Publish that on the internet

You will learn:

Designing responsive ECommerce website using Material UI like home page, product page, sidebar, and navbar.

Implementing frontend using NextJS like handling shopping cart, showing maps, beautiful charts.

Building Backend Web API using next connect and MongoDB to handle authentication, providing report data, handling products and orders.

Connecting to payment gateways like PayPal and make online payments.

Publishing your website on the cloud servers like Vercel and Netlify

This course is for all-levels developers who want to be a professional frontend developers and find a job in more than 22 M job opportunities around the world

You need to know the basics of Reactjs like components, state, props, and hooks to start this course.

Feel free to take a look at the course preview and enroll if it is along with your ambitions.

Who this course is for
Beginner JavaScript Programmers
Web Developers and Designers
Business owners who want to sell products

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/8c87ca4dc1f94a160e16bcbae45a7a10/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part1.rar.html
https://rapidgator.net/file/69e9aa3b3bd417d972387221d1babc73/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part2.rar.html
https://rapidgator.net/file/c0986416e4d0f7f2912db9c03d61478e/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part3.rar.html

uploadgig_com:
https://uploadgig.com/file/download/1AE438ca6Fec1322/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part1.rar
https://uploadgig.com/file/download/5BAfEf7c6d92d0c4/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part2.rar
https://uploadgig.com/file/download/A1e1f93f26e4c6fb/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part3.rar

nitroflare_com:
https://nitroflare.com/view/3ABCA96D87497A4/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part1.rar
https://nitroflare.com/view/219E0DF8ED4C6DE/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part2.rar
https://nitroflare.com/view/6438C28CD363DBF/be3ro.Next.Amazona.Build.ECommerce.Website.Like.Amazon.By.Next.JS.part3.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:30

What you'll learn

You will get to learn about the basics of pandas and python libraries, what it can offer, and what kind of problems could be solved using these libraries.
Data analysis and visualization using Pandas.

Requirements

Basic knowledge of Python and Mathematics
No prior information for machine learning is needed.
Basic computer programming terminologies.
Basic understanding of any of the programming languages is a plus.

Description

The goal of this course is to make the trainees expert on working with Pandas python libraries. This training will be helping folks to achieve proficiency in introducing the concept of data science with the help of libraries that we will be covering here. This course has been focused on training on Pandas. All the concepts that revolve around these libraries will be detailed very precisely through this course. The sole objective of this course is to enrich the trainees with the entire set of skills that are required to work with these python-based libraries. In this unit, you will get to learn about the basics of these libraries, what it can offer, and what kind of problems could be solved using these libraries. The initial hour in this unit has been given to explain the introduction while the rest of the time has been devoted to explaining the main concepts.

Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. This Python course will get you up and running with using Python for data analysis and visualization. The training will include the following:

Installing Jupyter

Jupyter Environment

Read data using Pandas

Series vs Data Frame

Basic Operations in Pandas

Analyze the imported data

Renaming Columns

Sorting

Filtering Data

Filtering Function

Read Selective Columns & Rows

Who this course is for:

This Pandas and NumPy Tutorial Course is designed for professionals with different backgrounds who are willing to learn data science in simple and easy steps using Python as a programming language. If you are into any kind of data and analytics work on any platform then this course is very useful for you
Managers and seniors should look up to this course as the current market is at its transition stage where you must have a good understanding of data and analysis techniques.
Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/dccb924a349352a0ff4450307fc1445a/9gfoh.Pandas.with.Python.for.Data.Science.part1.rar.html
https://rapidgator.net/file/b70ca38d272e6d8429fa5e5e0d8e64f5/9gfoh.Pandas.with.Python.for.Data.Science.part2.rar.html
https://rapidgator.net/file/09320e1255e9be5f587dd88c043ca215/9gfoh.Pandas.with.Python.for.Data.Science.part3.rar.html

uploadgig_com:
https://uploadgig.com/file/download/4D7aac7783ff7D95/9gfoh.Pandas.with.Python.for.Data.Science.part1.rar
https://uploadgig.com/file/download/ec5DCfede7F07859/9gfoh.Pandas.with.Python.for.Data.Science.part2.rar
https://uploadgig.com/file/download/Fb5ebF58010e68eD/9gfoh.Pandas.with.Python.for.Data.Science.part3.rar

nitroflare_com:
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https://nitroflare.com/view/56292AB155A209A/9gfoh.Pandas.with.Python.for.Data.Science.part2.rar
https://nitroflare.com/view/646E0D463515378/9gfoh.Pandas.with.Python.for.Data.Science.part3.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:36

What you'll learn:
Master IT auditing fundamentals and general audit processes for reporting
Gain the know-hows and practical knowledge in audit reporting/findings evaluation for Cyber and IT audits
Apply auditing concepts and technical knowledge in quizzes and learning scenarios
Know how to properly succeed in audit reporting phases of Cyber and IT audits

Requirements
None

Description
Are you interested in kick starting a career in IT auditing? Tired of learning IT auditing through theory and books? Then this is the perfect course for you! This is a condensed course to go over the basics and advanced concepts in IT auditing. The course is one of the first of its kind to not only cover concepts but to also walk you through practical examples and know-hows to conduct a Cyber and IT audit during the reporting stages. The course will also practical examples/templates prepare you to become a knowledgeable auditor in audit reporting.

Note: This course was just added on June 14. Captions and assignment will be updated/added by mid-July.

Your Instructor

Your instructor is a proven and skilled individual with over 6+ years of experience in big consulting, big4 accounting and big5 banks. Chris (The Technology Accountant) has worked in in-demand fields in consulting, advisory and assurance in Cyber and IT space. He holds a CPA (Chartered Professional Accountant), CISSP (Certified Information System Security Professional) and CISA (Certified Information System Auditor) designations and has taught over 20,000 students from 155+ countries on this platform.

Benefits to you

-Gain theoretical and practical knowledge of various auditing concepts

-Gain theoretical and practical knowledge and skills in conducting reporting through practices of;

a) 25+ practice exercise questions for audit reporting concepts and techncials

b) 7 downloadable course templates and detailed information for your learning/practice

c) Learning scenarios videos in course lectures

-Gain expert knowledge and material from proven Instructor

Accomplished Goals

At the end of this course, you would gain the fundamental and practical knowledge and skills in IT and Cyber audit reporting, you will also become prepared on how to formulate findings and audit reports with supporting examples/scenarios and templates. This course tnot only helps you audit but also effectively lead your audit engagements through reporting phases.

Topics covered in this course include:

1) Introduction to IT Audit Reporting

2) Basic auditing concepts

-Audit Lifecycle

-What is IT Audit Reporting

-Control Conclusions

-Exceptions vs Findings

-Audit Report (ie Components, Recipients,

-Types of Audit Reports

-Quality Control

3) Findings Evaluation

4) Audit Ratings

5) Audit Opinions

6) Findings Formulation/Evaluation (Reporting activities)

7) Findings Grid/Report (Reporting activities)

8) Audit Report (Reporting activities)

9) File Closure Checklist (Reporting activities)

10) Lessons Learnt Meeting (Reporting activities)

Who this course is for
Beginners/Intermediate students wanting to learn Cybersecurity and IT Audits
University and College students
Working Professionals (Business/IT)
Professionals supplementing their knOther Professionals: CPAs (Certified Public Accountants/Chartered Professional Accountants), CIAs (Certified Internal Auditors), CISM (Certified Information Security Manager), CISSP (Certified Information System Security Professional), ISO Auditors etcowledge to take professional IT audit exams

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/fe87df1c7d4ae8989268213b63601417/hg3dh.Practical.Guide.Cyber..IT.AuditingAudit.Reporting.rar.html

uploadgig_com:
https://uploadgig.com/file/download/86C25Cb09da0295d/hg3dh.Practical.Guide.Cyber..IT.AuditingAudit.Reporting.rar

nitroflare_com:
https://nitroflare.com/view/10A1C3FD9F3A4BB/hg3dh.Practical.Guide.Cyber..IT.AuditingAudit.Reporting.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:38

What you'll learn:
Microeconomics and Macroeconomics
How the capitalism and societies function
The role of government
Rationale decision-making
Fiscal and Monetary policies
Game Theory
The need for government intervention
Interest rate and money
Firm's Decisions

Requirements
2-dimensional Graph
Simple Mathematics

Description
THE MOST POPULAR ECONOMICS COURSE NOW ON UDEMY.

Last Updated: June 2021

This course will prepare you in the fundamental of Economics. It is taught at many introductory level modules at universities for business, economics, accounting, law, engineering, mathematics and even environmental studies. Understanding economics is the key essential skill in the modern world. The study of economics helps people understand the world around them. It enables people to understand people, decision-making, businesses, markets and government policies, and therefore better respond to the threats and opportunities that emerge when the broader economy and personal circumstances change. Topics includes scarcity, demand and supply, firm's cost structure, market structure, game theory, fiscal policy, monetary policy, economic growth, exchange rate and many more. The course will also explain the key historical economics events such as the 2008-2009 Global Financial Crisis and the 1997-1998 Asian Financial Crisis.

Unlike other courses, this course includes a comprehensive set of quizzes and assignments that are designed to assess your grasp of the key concepts. As we know, the best way to learn is to test yourself on the concepts.

This your chance to improve your employability, understanding of the world and make yourself think better with Economics. The structured curriculum will support you in completing the course in 10 weeks.

A lot of time and effort has been devoted into the production of the content in order to provide the best education for all who subscribes to the course. I hope that you this course will give you a better understanding of the world, make better decisions in life and look at the world in a different lens.

Quality education should be affordable and this course is now offered at a very affordable price.

Course Outline: Principles of Economics 101: Complete Micro & Macro

- MICROECONOMICS -

Scarcity

· Production Possibilities Frontier

· Specialisation and Gains from Trade

Market Forces

· Demand and Supply

· Elasticity

Producer Theory

· Profit Maximization

· Firm's Cost Structure

· Marginal Thinking

· Perfect Competition

· Monopoly

· Monopolistic Competition

· Oligopoly

· Shut-down Condition

· Sunk-Cost Fallacy

Game Theory

· Prisoner's Dilemma

· Nash Equilibrium and Dominant Strategy

- MACROECONOMICS -

Macroeconomic Measurements

· Macroeconomic Objectives

· Circular Flow of Income

· Macroeconomic Indicators: Production (GDP), Consumer Price Index, Inflation, Unemployment, Labour Force Participation Rate

Long-Run Macroeconomics

· Aggregate Production Function

· Explaining and Decomposing Economic Growth

· The Classical Long-Run Growth Model

· Capital Deepening

Short-Run Macroeconomics

· Economic Fluctuations

· The Short-Run (Keynesian Cross) Model

· Expenditure and Tax Multiplier Effects

· Fiscal Policy

Money and Banking

· The Nature of Money

· Banks in Money Creation

· Bank Runs, Role of the Central Bank in Financial Stability and Financial Intermediation

· The Instruments of Monetary Policy

· Money Demand and Supply

· Interaction between Money Market and Goods Market

· Conventional and Unconventional Monetary Policy

· 2008 - 2009 Global Financial Crisis

Currency Markets, Exchange Rates, and International Macroeconomics

· Currency Markets and Exchange Rates

· Government Intervention in Currency Markets

· Exchange Rates and the Trade Balance

· Purchasing Power Parity

· Impossible Trinity

· Exchange Rate and Output

· 1997-1998 Asian Financial Crisis

This is your opportunity. There is so much to gain.

Who this course is for
Individuals with no Economics background who wants to get started
Individuals who want to improve their understand of our society and economies

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/d0a928f727ce1df1bd2d16dfc6db4c41/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part1.rar.html
https://rapidgator.net/file/d2cd8e23738a44bb778c2894afeac5a8/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part2.rar.html

uploadgig_com:
https://uploadgig.com/file/download/F1bdef38F50858dB/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part1.rar
https://uploadgig.com/file/download/A686d10a65d22d80/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part2.rar

nitroflare_com:
https://nitroflare.com/view/7BAF5EE92E7A667/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part1.rar
https://nitroflare.com/view/8352C7BDA380FAB/srncy.Principles.of.Economics.101.Complete.Micro..Macro.part2.rar

Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:38

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.08 GB | Duration: 9h 52m

What you'll learn
Sap Business Analytics
Requirements
English Language
Basic Computer
Description
The SAP Business Analytics team, for its part, breaks down its SAP BusinessObjects product suite into six categories. (At SAP, business intelligence falls under the business analytics category. Got it?)

Here's a quick explainer on each product area.

1. Analytic Applications

The growing line of SAP BusinessObjects applications is classified by two categories. The first category is broken out by industry, such as financial services, manufacturing, consumer products, retail and utilities. Second, by line of business, which include: supply chain, finance, HR, IT, and service, sales and marketing.

2. Business Intelligence

The BI category (officially known as: SAP BusinessObjects Business Intelligence) encompasses five different product sets.

Reporting and Analysis. Includes: Crystal Reports, Web Intelligence, Predictive Workbench, and the SAP BusinessObjects Analysis editions for Microsoft and OLAP. Dashboards and Visualization. Includes: BusinessObjects Dashboards (formerly known as Xcelsius). Data Exploration. Includes: SAP BusinessObjects Explorer, and the "accelerated version" that uses in-memory analytics.

Mobile. Includes: SAP BusinessObjects Mobile.BI Platform. Includes: BI Platform product set, integration tools and Live Office for Microsoft product integration.

3. Enterprise Performance Management

So how's your company doing against the plan? How about the individual departments? The SAP EPM line includes key areas such as: strategy management; planning, budgeting and forecasting; profitability and cost management; financial consolidation; disclosure management; and supply chain performance.

4. Enterprise Information Management

SAP's EIM product set is wide ranging. The goal: to ensure good information can lead to good decisions.

Data Services. This categories include SAP BusinessObjects products for (among others) data integration, delivery, federation, insight and quality management.Master Data Management. Two products here: NetWeaver Master Data Management and Master Data Governance. Event Processing. Two product categories here, too: BusinessObjects Event Insight and Sybase Aleri Streaming Platform.Content Management. Three OpenText products aim to help companies manage their structured and unstructured content. Information Governance. Just one product here: NetWeaver Information Lifecycle Management.

5. Governance, Risk and Compliance

The GRC category includes enterprise GRC (risk management, compliance, and monitoring), access risk management (centralized GRC management), global trade services (managing worldwide compliance risks), and sustainability performance management.

6. Data Warehousing

This category includes the HANA in-memory computing appliance; enterprise data warehouses and data marts; Sybase IQ; and the NetWeaver Business Warehouse and Business Warehouse Accelerator.

Who this course is for:
Professionals
Officials
Professors
Industrials
Technology Experts
Technical Students
Researchers
Data Scientists
SAP Programmers
Data Engineers
Cloud users
SAP users
Analysts
Business Intelligence Analysts
Software Engineering Researchers

Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/8ceb6b0ac3b61eaa4742d4d3bf686d48/rqgt7.Professional.Program.on.SAP.for.Business.Analytics.PPSBA.part1.rar.html
https://rapidgator.net/file/9dbd9648867b0bf137e682867088ebb1/rqgt7.Professional.Program.on.SAP.for.Business.Analytics.PPSBA.part2.rar.html
https://rapidgator.net/file/4a9acda582be173896fa655b58130741/rqgt7.Professional.Program.on.SAP.for.Business.Analytics.PPSBA.part3.rar.html
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:39

What you'll learn

Sap Materials Management
SAP WM

Requirements

Basic English
Basic Computer Science

Description

SAP MM (Materials Management)

SAP MM (Materials Management) is a module in SAP ERP Central Component (ECC) that provides companies with materials, inventory and warehouse management capabilities. The primary goal of SAP MM is to make sure that materials are always kept in proper quantities and without shortages or gaps in the organization's supply chain. It also helps supply chain professionals and other SAP users complete the purchasing of goods in a timely and cost-effective way and to be able to deal with day-to-day changes in these processes. One of the critical modules in SAP ECC, SAP MM is part of SAP ECC's logistics function and plays a vital role in a manufacturer's supply chain. It integrates with other ECC components like Production Planning (PP), Sales and Distribution (SD), Plant Maintenance (PM), Quality Management (QM), Finance and Controlling (FICO) and Human Capital Management (HCM). Support for SAP ECC is scheduled to stop in 2025, at which point it will be replaced by SAP S/4HANA. It's not clear from SAP how the functions of MM will transition to S/4HANA, although the newer platform has components to address the core issues behind MM. SAP MM submodules SAP MM's functions include material management, procurement process management, master data management (material and vendor master), inventory management, material requirements planning and invoice verification. All of these MM submodules have functions that perform specific business processes for those modules. These are executed through transactions, the method that SAP ECC uses to complete business processes. MM also supports other logistics functions that require materials information, such as plant maintenance and project management. Business benefits of SAP MM Everything in MM revolves around master data, which is stored and manipulated in centralized master-data tables. Master data types include materials master, work center, bill of materials and routing. The master data is used to create transactional data in SAP ECC. For example, when a production order is created in PP, it uses master data from MM about the raw materials needed to produce the finished product, which will subsequently be used to create a sales order in SD.

Warehouse Management System (WMS)

Purpose

The SAP Warehouse Management system (WMS) provides flexible, automated support in processing all goods movements and in managing stocks in your warehouse complex. The system supports scheduled and efficient processing of all logistics processes within your warehouse.

Implementation Considerations

If you manage your warehouse stocks with SAP Inventory Management (MM-IM), you manage the quantities and values of stocks in several storage locations.

In comparison, the WMS allows you to map your entire warehouse complex in detail to storage bin level. Not only do you gain an overview of the entire quantity of a material in the warehouse; you can also always determine exactly where a certain material currently is in your warehouse complex. With the WMS you can optimize the use of all of your storage bins and warehouse movements, and store material stocks from several plants together in warehouses with random storage.

Integration

The WMS is fully integrated into the SAP environment. Business processes, which you trigger in other application components, lead to physical goods movements in your warehouse. You organize, control, and monitor these goods movements with the WMS.

Storage Bin Management

You map your entire storage facilities in the Warehouse Management system. In doing so, you can set up various storage facilities such as automatic warehouse, high rack storage areas, bulk storage or fixed storage bins in various storage types, according to your needs.

You manage material stocks at storage bin level. You can define these storage bins according to your own requirements. Every storage bin in your warehouse is mapped in the system. This lets you monitor all warehouse movements at all times. You can follow where a certain material is in your warehouse.

SAP Inventory Management and the SAP Warehouse Management system are fully integrated. With its inventory procedure and recording of stock differences, the system ensures that the inventory balance in Inventory Management always corresponds to the warehouse stock in the WMS.

Goods Movements

You process all goods movements that affect your warehouse via the WMS. This includes goods receipts, goods issues, stock transfers, material staging for production, automatic replenishment, managing hazardous materials, and processing stock differences in your warehouse.

The WMS optimizes warehouse capacities and material flows using putaway and stock removal strategies, which you can adjust to suit your individual needs, or by using storage units.

Planning and Monitoring

The WMS offers you an overview of all goods issues and warehouse stocks. The system supports you in planning, monitoring, and optimizing work processes. For example, it gives you a foresighted view of the workload in the coming days or allows you to intervene in good time during critical warehouse processes, so that you can execute warehouse movements on time. Via the RF monitor, you get an up-to-date picture of all of the activities in the warehouse, which means that you can control the actual work in the warehouse using the RF monitor.

Radio Frequency Connection

In order to structure the work in the warehouse efficiently and cost-effectively, you control the warehouse workers' work steps clearly and simply via mobile radio-frequency terminals.

Radio frequency connection (RF connection) to mobile date entry achieves quick and flawless data transfer. The RF machines receive data directly from the SAP system and transfer data back to the system. Using barcodes, you can record information to be recorded and verify it. This means that you ensure a high standard of quality in your warehouse.

Decentralized WMS

You can run the WMS as a standalone decentralized warehouse management system, independent of a central enterprise resource planning system (ERP system). For more information, see Decentralized Warehouse Management.

Warehouse Control

WMS also has an interface to external systems (warehouse control units), so that you can integrate automatic putaway, stock removal systems or fork lift control systems into the warehouse management system for all warehouse movements with the help of this ALE interface.

Who this course is for:

Anyone interested
SAP Professionals
College Students
Office Trainees
SAP Experts

Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/7a4e1d651466e6a996931fcac708737d/ipc4w.Professional.Training.on.SAP.MM.PTSMM.part1.rar.html
https://rapidgator.net/file/3117ea1f2dd96e171b9b6de44a74d85a/ipc4w.Professional.Training.on.SAP.MM.PTSMM.part2.rar.html
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nitroflare_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:40

What you'll learn

The skills related to development, big data, and the Hadoop ecosystem and the knowledge of Hadoop and analytics concepts are the tangible skills that you can learn from these PySpark Tutorials.
You will also learn how parallel programming and in-memory computation will be performed
Learn Recency Frequency Monetary segmentation (RFM). RFM analysis is typically used to identify outstanding customer groups further we shall also look at K-means

Requirements

The pre-requisite of these PySpark Tutorials is not much except for that the person should be well familiar and should have a great hands-on experience in any of the languages such as Java, Python or Scala or their equivalent. The other pre-requisites include the development background and the sound and fundamental knowledge of big data concepts and ecosystem as Spark API is based on top of big data Hadoop only. Others include the knowledge of real-time streaming and how big data works along with a sound knowledge of analytics and the quality of prediction related to the machine learning model.

Description

This module in the PySpark tutorials section will help you learn about certain advanced concepts of PySpark. In the first section of these advanced tutorials, we will be performing a Recency Frequency Monetary segmentation (RFM). RFM analysis is typically used to identify outstanding customer groups further we shall also look at K-means clustering. Next up in these PySpark tutorials is learning Text Mining and using Monte Carlo Simulation from scratch.

Pyspark is a big data solution that is applicable for real-time streaming using Python programming language and provides a better and efficient way to do all kinds of calculations and computations. It is also probably the best solution in the market as it is interoperable i.e. Pyspark can easily be managed along with other technologies and other components of the entire pipeline. The earlier big data and Hadoop techniques included batch time processing techniques.

Pyspark is an open-source program where all the codebase is written in Python which is used to perform mainly all the data-intensive and machine learning operations. It has been widely used and has started to become popular in the industry and therefore Pyspark can be seen replacing other spark-based components such as the ones working with Java or Scala. One unique feature which comes along with Pyspark is the use of datasets and not data frames as the latter is not provided by Pyspark. Practitioners need more tools that are often more reliable and faster when it comes to streaming real-time data. The earlier tools such as Map-reduce made use of the map and the reduced concepts which included using the mappers, then shuffling or sorting, and then reducing them into a single entity. This MapReduce provided a way of parallel computation and calculation. The Pyspark makes use of in-memory techniques that don't make use of the space storage being put into the hard disk. It provides a general purpose and a faster computation unit.

The career benefits of these PySpark Tutorials are many. Apache spark is among the newest technologies and possibly the best solution in the market available today when it comes to real-time programming and processing. There are still very few numbers of people who have a very sound knowledge of Apache spark and its essentials, thereby an increase in the demand for the resources is huge whereas the supply is very limited. If you are planning to make a career in this technology there can be no wiser decision than this. The only thing you need to keep in mind while making a transition in this technology is that it is more of a development role and therefore if you have a good coding practice and a mindset then these PySpark Tutorials are for you. We also have many certifications for apache spark which will enhance your resume.

Who this course is for:

The target audience for these PySpark Tutorials includes ones such as the developers, analysts, software programmers, consultants, data engineers, data scientists , data analysts, software engineers, Big data programmers, Hadoop developers. Other audience includes ones such as students and entrepreneurs who are looking to create something of their own in the space of big data.
Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/a0b17dfacda71f69ff16fbc789abb74e/skxbf.PySpark.for.Data.Science..Advanced.rar.html

uploadgig_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:41

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 16 lectures (2 hour, 19 mins) | Size: 898 MB
Learn basics of Apache Spark and learn to analyze Big Data for Machine Learning using Python in PySpark

What you'll learn

Learn bout the concept of RDDs and other very basic features and terminologies being used in the case of Spark
You will also understand what are the benefits and disadvantages of using Spark
Use Python with Big Data on Apache Spark
These PySpark Tutorials aims to explain the basics of Apache Spark and the essentials related to it

Requirements

The pre-requisite of these PySpark Tutorials is not much except for that the person should be well familiar and should have a great hands-on experience in any of the languages such as Java, Python or Scala or their equivalent. The other pre-requisites include the development background and the sound and fundamental knowledge of big data concepts and ecosystem as Spark API is based on top of big data Hadoop only. Others include the knowledge of real-time streaming and how big data works along with a sound knowledge of analytics and the quality of prediction related to the machine learning model.

Description

These PySpark Tutorials aim to explain the basics of Apache Spark and the essentials related to it. This also targets why the Apache spark is a better choice than Hadoop and is the best solution when it comes to real-time processing. You will also understand what are the benefits and disadvantages of using Spark with all the above-listed languages You will also read about the concept of RDDs and other very basic features and terminologies being used in the case of Spark. This course is for students, professionals, and aspiring data scientists who want to get hands-on training in PySpark (Python for Apache Spark) using real-world datasets and applicable coding knowledge that you'll use every day as a data scientist.

Pyspark is a big data solution that is applicable for real-time streaming using Python programming language and provides a better and efficient way to do all kinds of calculations and computations. It is also probably the best solution in the market as it is interoperable i.e. Pyspark can easily be managed along with other technologies and other components of the entire pipeline. The earlier big data and Hadoop techniques included batch time processing techniques.

Pyspark is an open-source program where all the codebase is written in Python which is used to perform mainly all the data-intensive and machine learning operations. It has been widely used and has started to become popular in the industry and therefore Pyspark can be seen replacing other spark-based components such as the ones working with Java or Scala. One unique feature which comes along with Pyspark is the use of datasets and not data frames as the latter is not provided by Pyspark. Practitioners need more tools that are often more reliable and faster when it comes to streaming real-time data. The earlier tools such as Map-reduce made use of the map and the reduced concepts which included using the mappers, then shuffling or sorting, and then reducing them into a single entity. This MapReduce provided a way of parallel computation and calculation. The Pyspark makes use of in-memory techniques that don't make use of the space storage being put into the hard disk. It provides a general purpose and a faster computation unit.
Who this course is for:

The target audience for these PySpark Tutorials includes ones such as the developers, analysts, software programmers, consultants, data engineers
Other audience includes ones such as students and entrepreneurs who are looking to create something of their own in the space of big data.
Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/19f1b6854a7d3edfd2c53f4c0fc35962/cp888.PySpark.for.Data.Science..Beginners.rar.html

uploadgig_com:
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nitroflare_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:42

What you'll learn

This module on PySpark Tutorials aims to explain the intermediate concepts such as those like the use of Spark session in case of later versions and the use of Spark Config and Spark Context in case of earlier versions.
his will also help you in understanding how the Spark related environment is set up, concepts of Broadcasting and accumulator, other optimization techniques include those like parallelism, tungsten, and catalyst optimizer.

Requirements

The pre-requisite of these PySpark Tutorials is not much except for that the person should be well familiar and should have a great hands-on experience in any of the languages such as Java, Python or Scala or their equivalent. The other pre-requisites include the development background and the sound and fundamental knowledge of big data concepts and ecosystem as Spark API is based on top of big data Hadoop only. Others include the knowledge of real-time streaming and how big data works along with a sound knowledge of analytics and the quality of prediction related to the machine learning model.

Description

This module on PySpark Tutorials aims to explain the intermediate concepts such as those like the use of Spark session in case of later versions and the use of Spark Config and Spark Context in case of earlier versions. This will also help you in understanding how the Spark-related environment is set up, concepts of Broadcasting and accumulator, other optimization techniques include those like parallelism, tungsten, and catalyst optimizer. You will also be taught about the various compression techniques such as Snappy and Zlib. We will also understand and talk about the various Big data ecosystem related concepts such as HDFS and block storage, various components of Spark such as Spark Core, Mila, GraphX, R, Streaming, SQL, etc. and will also study the basics of Python language which is related and relevant to be used along with Apache Spark thereby making it Pyspark. We will learn the following in this course:

Regression

Linear Regression

Output Column

Test Data

Prediction

Generalized Linear Regression

Forest Regression

Classification

Binomial Logistic Regression

Multinomial Logistic Regression

Decision Tree

Random Forest

Clustering

K-Means Model

Pyspark is a big data solution that is applicable for real-time streaming using Python programming language and provides a better and efficient way to do all kinds of calculations and computations. It is also probably the best solution in the market as it is interoperable i.e. Pyspark can easily be managed along with other technologies and other components of the entire pipeline. The earlier big data and Hadoop techniques included batch time processing techniques.

Pyspark is an open-source program where all the codebase is written in Python which is used to perform mainly all the data-intensive and machine learning operations. It has been widely used and has started to become popular in the industry and therefore Pyspark can be seen replacing other spark based components such as the ones working with Java or Scala. One unique feature which comes along with Pyspark is the use of datasets and not data frames as the latter is not provided by Pyspark. Practitioners need more tools that are often more reliable and faster when it comes to streaming real-time data. The earlier tools such as Map-reduce made use of the map and the reduce concepts which included using the mappers, then shuffling or sorting and then reducing them into a single entity. This MapReduce provided a way of parallel computation and calculation. The Pyspark makes use of in-memory techniques that don't make use of the space storage being put into the hard disk. It provides a general-purpose and a faster computation unit.
Who this course is for:

The target audience for these PySpark Tutorials includes ones such as the developers, analysts, software programmers, consultants, data engineers, data scientists , data analysts, software engineers, Big data programmers, Hadoop developers. Other audience includes ones such as students and entrepreneurs who are looking to create something of their own in the space of big data.
Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/a13b10b1b7f74777714b1ade80434623/3g0hj.PySpark.for.Data.Science..Intermediate.part1.rar.html
https://rapidgator.net/file/26767e654c35524806b6773b766197dd/3g0hj.PySpark.for.Data.Science..Intermediate.part2.rar.html

uploadgig_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:43

What you'll learn

One will learn about different types of visualizations, things to keep in mind before choosing the type of visualization, customizing visualizations, use of color palettes, etc which are going to be very useful skills that are very much in demand these days.
Under this part of the training program, advanced concepts of seaborn tool that are an introduction to seaborn advance, building structure multiDescription grids, conditional small multiplies, use of custom functions, Descriptionting pairwise data relationships, choosing color palettes, use of different seaborn figure styles, setting different color palettes, use of reference files in advance, etc.

Requirements

The basic prerequisite for this course is that the student or the professional should have a basic knowledge and understanding of the machine learning tools and techniques and also should have a basic knowledge and overview of the data science techniques. Apart from this, he should also be aware of the basic analytical concepts which are a must while opting for this course. The user should also have a mathematical background as most of the algorithms being used and the concepts which are discussed are mathematics-based.

Description

There are a variety of skills that participants will learn through this training program like visualizing statistical relationships, different types of visualizations, scatter Descriptions, Descriptionting with categorical data, bar Descriptions, color palettes, visualizing linear relationships, bivariate distributions, univariate distributions, visualizing the distribution of a data set, cat Description, strike Description, etc.

What's the training gets completed the learners can easily enter the industry as a data analyst, business analyst, statistician, quality engineer, quality manager, consultant, team leader, statistical analyst, software test engineer, QA engineer, consultant, analytics manager, and many other diverse fields are open for individuals to show their potential and skills in the world.

Under this part of the training program, advanced concepts of seaborn tool that are an introduction to seaborn advance, building structure multiDescription grids, conditional small multiplies, use of custom functions, Descriptionting pairwise data relationships, choosing color palettes, use of different seaborn figure styles, setting different color palettes, use of reference files in advance, etc.

In the domain of analytics and data science, there are a huge number of libraries that are gaining huge popularity with every passing day due to their wide array of benefits and the features that they have to offer. One such important library is matDescriptionlib of which seaborn is made up. These libraries together are used for visualizations and making a good level of predictions which is specifically based on the outcome of data. These Descriptions help analyze and determine the nature of the data and how it can be used for better use. Seaborn is Python-based which is built on top of MatDescriptionlib, therefore, it consists of all the features which are present with the main libraries. Seaborn libraries help in resolving two fundamental issues that are related to default matDescriptionlib parameters and the ones related to working with data frames and therefore hold a higher value than the parent library.

Who this course is for:

The target audience becomes anybody who is interested in learning this Python Seaborn Tutorial and follows the above-mentioned pre-requisites. This typically includes professionals such as data scientists, data engineers, analysts, consultants, software developers, software engineers, testers. Apart from these professionals everybody who is working to build something of their own such as an entrepreneur forms an ideal part of the audience and also the students whether they are directly college passed outs or are looking to do something much more creative and bigger can make use of this course in a much wiser manner.
Screenshots

Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/2d468617b05f04cc214b186b02bcaa26/6uf17.Python.Data.Visualization.using.Seaborn..Advanced.rar.html

uploadgig_com:
https://uploadgig.com/file/download/5f6ef8ce033Ad616/6uf17.Python.Data.Visualization.using.Seaborn..Advanced.rar

nitroflare_com:
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Links are Interchangeable - No Password - Single Extraction

mitsumi1 · 21.07.2021, 01:44

What you'll learn

One will learn about introduction to seaborn, review of the training, different types of Descriptions, distribution Description, scatterDescription and heat map, case studies of scatter Description, boxDescription, bank problem, case study on swarm Description, etc.
Other skills that are going to be covered under this training program is visualizing statistical relationships which include scatterDescriptions, line Descriptions, Descriptionting with categorical data, showing multiple relationships with facets, categorical scatter Descriptions, distribution of observations with categories, statistical estimation with categories, count Description, point Description, boxDescription, bar Description, use of reference files, etc.

Requirements

The user should also have a mathematical background as most of the algorithms being used and the concepts which are discussed are mathematics-based.
The basic prerequisite for this course is that the student or the professional should have a basic knowledge and understanding of the machine learning tools and techniques and also should have a basic knowledge and overview of the data science techniques. Apart from this, he should also be aware of the basic analytical concepts which are a must while opting for this course.

Description

As training goes ahead, individuals will start realizing the importance and value of seaborn training with diverse skills and concepts that are going to be taught under this training program. The curriculum of the training program is developed in such a way that it helps in getting all the industry requirements and also takes squares of individuals' requirements who are investing their time and efforts in learning something new and interesting. The core skills that are going to be covered under this training program are as follows:

Introduction of Seaborn

Visualizing Statistical Relationships

Scatter Description

Line Descriptions

Descriptionting with Categorical Data

Showing Multiple Relationships with Facets

Categorical ScatterDescriptions

Distributions of Observations within Categories

Statistical Estimation within Categories

CountDescription

PointDescription

BoxenDescription

ViolenDescription

BarDescription

SwarmDescription

StripDescription

CatDescription

One will learn about introduction to seaborn, o review of the training, different types of Descriptions, distribution Description, scatterDescription and heat map, case studies of scatter Description, boxDescription, bank problem, case study on swarm Description, etc.

Other skills that are going to be covered under this training program is visualizing statistical relationships which include scatterDescriptions, line Descriptions, Descriptionting with categorical data, showing multiple relationships with facets, categorical scatter Descriptions, distribution of observations with categories, statistical estimation with categories, count Description, point Description, boxDescription, bar Description, use of reference files, etc.
Who this course is for:

Data scientists, data engineers, analysts, consultants, software developers, software engineers, testers.
The target audience becomes anybody who is interested in learning this Python Seaborn Tutorial and follows the above-mentioned pre-requisites
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Download link:

Код:

rapidgator_net:
https://rapidgator.net/file/963e10053519dec693e95bd1ed4504ed/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part1.rar.html
https://rapidgator.net/file/003a635df3d86e73de1d57993c92dec6/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part2.rar.html

uploadgig_com:
https://uploadgig.com/file/download/Ce129f745F02f2e9/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part1.rar
https://uploadgig.com/file/download/9D5d3578147c200b/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part2.rar

nitroflare_com:
https://nitroflare.com/view/C238AABAA0F7F30/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part1.rar
https://nitroflare.com/view/3869A3B6B82F3C1/pcxv6.Python.Data.Visualization.using.Seaborn..Beginners.part2.rar

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