Learn Python by making games



Learn Python by making games
Published 07/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 9.01 GB | Duration: 138 lectures • 26h 43m



What you'll learn
You will learn how to use Python effectively
You will create a portfolio of python games
You will learn how to manage large project well
You will learn object-oriented programming
You will learn and implement advanced Python features
You will develop a thorough understanding of Python

Requirements
Access to some kind of computer

Description
Learn the world's most popular programming language by making games!
This course includes an incredibly comprehensive, yet easy to follow, introduction to Python and uses that knowledge to create 4 sophisticated games. By the time you finish these projects you will have a strong understanding of Python and of coding in general. You will also have amazing projects for your portfolio.
The course contains over 130 videos and includes a huge amount of exercises so you can practice while you code along. You can also find the code for every video attach in the course. The course will start completely from scratch and I will begin by installing Python on Windows or MacOS; or you can use an online code editor. If you are in doubt, the entire first 11 hours are freely available both here on Udemy and on YouTube.
This course is going to cover every topic of Python, for example
All of the datatypes (integers, strings, floats, booleans, lists, tuples, dictionaries etc)
You will learn classes and object-oriented programming
Inheritance, both simple and complex will be covered in detail
You will learn how to control the flow of the code using if, while, for and match
You will learn about functions and how to pass information around
There are many sections on scope to keep your code organized
Decorators will be covered in depth
File handling will be used
Python is one of the most desirable features on the job market and can get you into well-paying and interesting jobs. It is also a very easy to learn language that you can use as a starting point in your coding career. I am looking forward to seeing you in the course!
Who this course is for
Everyone interested in programming

BASH Scripting Using Cryptocurrency APIs



Bash Scripting Using Cryptocurrency Apis
Published 7/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.58 GB | Duration: 11h 45m

Learn how to use BASH through example by creating practical and usable scripts with cryptocurrency APIs.


What you'll learn
Learn about BASH scripting using practical examples
Create scripts using cryptocurrency APIs
Create a foundation for future BASH scripting
Have knowledge of BASH, Linux, and cryptocurrency by end of the course

Requirements
No prerequisites for taking this course but all levels will benefit

Description
This course is designed for all levels from the beginner student interested in learning how to create scripts and code in the terminal using BASH*to the advanced student who wants to add more BASH*skills to their tool belt. In this unique course, you will learn many BASH scripts that are reusable and applicable to various functions that involve pulling information from cryptocurrency APIs. This course applies a unique method of learning through practical and usable examples which will provide reusable code for future scripts and projects. By completing this course, you will advance your efficiency with BASH; become skilled using Linux (Ubuntu) and virtual machines; and even gain some knowledge as a cryptocurrency investor along the way. Some examples include learning to code colored cryptocurrency running tickers and cryptocurrency price projection scripts. These practical and exciting examples will supercharge your learning process in an enjoyable and efficient way. This course is compatible with every Operating System (Windows, Mac OSX, and Linux). This course was crafted by an instructor who is a Certified Linux System Administrator, a Web 2 and Web 3 Developer, and a cryptocurrency consultant with over ten years of experience in BASH. Created with the student in mind, jump right in to coding rewarding scripts and enjoy learning by creating!
Overview
Section 1: Introduction
Lecture 1 About Me and My Motivation For Creating This Course
Section 2: FOR MAC USERS
Lecture 2 VirtualBox or MacOS Terminal
Lecture 3 Installing Homebrew and jq
Section 3: VirtualBox Tutorial
Lecture 4 Installing Ubuntu On VirtualBox
Lecture 5 Enabling VirtualBox Clipboard Part 1
Lecture 6 Enabling VirtualBox Clipboard Part 2
Lecture 7 Enable USB On VIrtualBox
Lecture 8 VirtualBox Workflow Overview
Section 4: Intro to API Requests Using Coinbase API
Lecture 9 Get BTC Price Using curl
Lecture 10 API URL for Variable Tickers
Lecture 11 Intro to jq
Section 5: BASH Script Basics
Lecture 12 First BASH Script
Lecture 13 First Parameter
Lecture 14 Multiple Prices with For In Loop
Section 6: Price Grab Script
Lecture 15 Add Ticker Name
Lecture 16 Uppercase to Lowercase with tr
Lecture 17 If Then Whitespace Logic with wc Part 1
Lecture 18 If Then Whitespace Logic with wc Part 2
Section 7: Running Crypto Price Ticker Script
Lecture 19 Run Ticker with Nested Loop
Lecture 20 Add User Inputted Sleep Time
Lecture 21 Variables For Coloring Ticker
Lecture 22 Organizing Script with Comments
Lecture 23 Declare First Function
Lecture 24 Color Price
Lecture 25 Explanation of Script Code
Lecture 26 Finishing Touches
Lecture 27 Declare Command Scope
Section 8: Coin Gecko API
Lecture 28 API Intro
Lecture 29 coins/markets jq
Lecture 30 More Advanced jq
Section 9: Terminal-Based Coin Gecko Script
Lecture 31 Outputting Top Crypto Names
Lecture 32 Add Rank and Price Data
Lecture 33 Add Market Cap to Row
Lecture 34 Beginning Large Number Logic
Lecture 35 Suffix Number Script
Lecture 36 printf Rounding
Lecture 37 Large Number Logic
Lecture 38 Finish Suffix Number Script
Lecture 39 Add Suffix Number Logic to tcmc
Lecture 40 Finish Terminal-Based Coin Gecko Script
Lecture 41 tcmc and Suffix Number Review
Lecture 42 MAC USERS Running tcmc2 on Mac Fix
Section 10: Price Predictor Script
Lecture 43 Overview
Lecture 44 Ticker Data as JSON Variable
Lecture 45 Testing Predicted Price Logic
Lecture 46 Rounding Predicted Price
Lecture 47 Styling Predicted Price
Lecture 48 Column Output and Finalizing Script
Section 11: Projected Total Market Cap Price Predictor Script
Lecture 49 Get Total Market Cap and Suffix Number
Lecture 50 Predicted Total Market Cap Input Checking
Lecture 51 Expanded Input Checking
Lecture 52 Predicted Total Market Cap Calc Function Part 1
Lecture 53 Predicted Total Market Cap Calc Function Part 2
Lecture 54 Add Offset to Loop For Predicted Calculations
Lecture 55 Debugging
Lecture 56 Completing Script Logic
Lecture 57 Extra SHIB or Exponential Price Logic
Lecture 58 Logic for Exponential Tickers or SHIB
Lecture 59 Clean Up Test echo Statements
Lecture 60 Debugging and Header Styling
Lecture 61 Finalizing Output Logic
Lecture 62 Finializing Script
Lecture 63 MAC USERS Run Script on Mac Fix
Section 12: Price History Script
Lecture 64 Price History Script
Section 13: Portfolio Tracker
Lecture 65 Part 1
Lecture 66 Part 2
Lecture 67 Part 3
Lecture 68 Part 4
Section 14: Portfolio Tracker Using Block Explorers
Lecture 69 Column Headers and First Block Explorer
Lecture 70 Get BTC Data and Format
Lecture 71 Output Formatting
Lecture 72 Add ETH to Portfolio
Lecture 73 Add ALGO to Portfolio
Lecture 74 Encrypt Script
Lecture 75 Run Encrypted Script
Lecture 76 MAC USERS Run Encrypted Script on Mac Fix
People with interest in BASH, Linux and cryptocurrency

Iatf 16949 Core Tools - Statistical Process Control (Spc)



Iatf 16949 Core Tools - Statistical Process Control (Spc)
Last updated 5/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.48 GB | Duration: 5h 43m

Detailed understanding and Excel work book on Statistical Process Control (SPC) in line with AIAG SPC Manual-2nd edn.



What you'll learn
1. Method and techniques of Statistical Process Control (SPC) documentation and implementation in real scenario.
3. Use of Microsoft excel templates and files to practice these tools and integrating with PPAP (Production Part Approval Process) submission.
4. Use of MINITAB software for SPC.


Requirements
1. Degree / Diploma in science or engineering.
2. Have a preliminary awareness of IATF 16949-2016 QMS standard (desirable).
3. Analytical and logical approach in understanding technical subjects.
4. Some work experience in one or more technical functions in the company (desirable).
5. Preliminary understanding of simple product drawings, specifications, measurement methods, check sheets / technical records related to manufacturing process.
6. Preliminary working knowledge in Microsoft Excel (desirable).


Description
Complete explanation and demonstration with example as required on IATF Core Tools for Statistical Process Control (SPC). This will be equivalent to one full day instructor led training, which you can complete at your convenient time. Downloadable excel files and PDF files are provided which you can use for making practicing this core tool effectively for your organization's manufacturing area and to enhance knowledge on this subjects. Further you can strengthen your hands on experience which has no substitute.Also use of Minitab software is shown for SPC.

Overview
Section 1: Introduction to SPC.

Lecture 1 Overview of the training programme.

Lecture 2 Purpose of SPC in automotive manufacturing.

Section 2: Practicing Statistical Process Control (SPC).

Lecture 3 Basic understanding of SPC.

Lecture 4 Steps for Variable control chart - X-bar/R.

Lecture 5 Making X-bar/R - control chart in shop floor.

Lecture 6 Calculation of Control Limits for X-bar/R - control chart.

Lecture 7 Analysis of chart and correcting the control limits.

Lecture 8 Implementation of SPC as control method.

Lecture 9 Other variable control charts.

Lecture 10 Attribute control charts.

Section 3: Managerial aspects of SPC.

Lecture 11 Process capability and performance.

Lecture 12 Over-adjustment.

Lecture 13 Selection of appropriate control chart.

Section 4: Spotlight Control charts and Pre-control.

Lecture 14 Stoplight and Pre-Control methods.

Section 5: Summary of the program.

Lecture 15 Summary of SPC.

Section 6: Bonus lecture - 1: Use of Minitab in SPC

Lecture 16 Use of Minitab for SPC

1. Persons holding executive responsibility in Quality, Manufacturing, Engineering function of automotive manufacturing industries.,2. Young engineers and scientists working in automotive industries and looking for career enhancement.,3. Department Head / Training Head may offer this program to his / her subordinates for effective training without sending the persons outside for training.,4. Senior Technical Persons of the company who wants to provide internal training to the junior executives for working as a team and for making PPAP documentation.

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The Production Part Approval Process (PPAP)



The Production Part Approval Process (PPAP)
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 3.23 GB | Duration: 3h 40m

The Product Part Approval Process, commonly called "PPAP", is used around the world in a variety of industries including automotive, aerospace, appliance, agriculture, and heavy truck as the "final gate" before launching a new part into production.




What you'll learn

The Production Part Approval Process, PPAP

The 18 core elements of PPAP

Where and when PPAP are used

The benefits of PPAP

An explanation of the 5 PPAP levels

A review of the Process FMEA, Design FMEA, Measurement System Analysis, Process Control Plan, and the other PPAP documents

A review of an actual completed PPAP package

A review of able Excel templates of the PPAP forms


Requirements

General knowledge of manufacturing

General knowledge of new product launches


Description

The purpose of thee PPAP system is to 1) detee if the supplier understands the part's eeering requirements, and 2) if the supplier is capable of consistently meeting those requirements.

You will learn how and why to use PPAP, the benefits of the system, and a detailed overview of each of the core 18 elements including:

1. Design record

2. Authorized Eeering Change Documents

3. Customer Eeering Approval

4. Design Failure Mode and Effects Analysis (DFMEA)

5. Process Flow Diagram (PFD)

6. Process Failure Mode and Effects Analysis (PFMEA)

7. Process Control Plan

8. Measurement System Analysis (MSA) Studies

9. Dimensional Results

10. Material and Performance Test Results

11. Initial Process Studies

12. Qualified Laboratory Documentation

13. Appearance Approval Report (AAR)

14. Sample Production Parts

15. Master Sample

16. Checking Aids

17. Customer-specific Requirements

18. Part Submission Warrant (PSW)

By signing up for this class, you not only get 2+ hours of high-quality, practical training on the PPAP system, but also a set of PPAP templates that you can and adapt to your own organization.

PPAP skills are an essential part of the quality professional's skill set. They are in demand and highly transferable across industries and organizations. The working knowledge of PPAP's you gain in this class will give you the "upper hand" you've been looking for to advance your career.

The class is also fully aligned with the AIAG PPAP manual, and will also fulfill the "Core Tools" auditor training as required by IATF 16949:2016.

Regardless of your industry, if you're looking for solid training on the established PPAP process (without breaking you bank), this is the class for you!! Sign up today.


Who this course is for:

Quality managers

Quality eeers

Quality auditors

New product launch specialists

Supply chain professionals

Manufacturing professionals

IATF 16949 Core Tool-Advanced Product Quality Planning-APQP



IATF 16949 Core Tool-Advanced Product Quality Planning-APQP
Iatf 16949 Core Tool-Advanced Product Quality Planning-Apqp
Last updated 6/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.30 GB | Duration: 4h 21m

Complete guide & EXCEL files for effective APQP process.



What you'll learn

Clear understanding of various elements of APQP process.

Will be able to prepare and review APQP document effectively and coordinate with core team to improve effectiveness of product design and development activities.

Will be able to review the APQP of suppliers effectively.

Will be able to formulate effective CONTROL PLAN for different types of processes.


Requirements

Person should have a degree / diploma in science / engineering / technology.

Person should have some involvement in operational function of the company such as production, quality assurance, engineering, design, testing, inspection, supplier assessment etc.

Person should be familiar with working in excel for making simple documentation, calculation, formatting etc.

An awareness of Quality Management System, such as ISO 9001, IATF 16949 would be added advantage.

Should cultivate team work in organization.


Description

The course material is organized in sequence of several sections and sub-sections.The basic understanding is elaborated in each sections, so that even a new comer can follow the course easily.The sections which are related to preparation of APQP documents are elaborated in details with examples in excel sheet, which can be used for practical applications.At the end there is a Quiz section, which will help recaps of the key understanding of various sections.Downloadable materials are provided which are useful for technical knowledge, practicing APQP activity and necessary documentation.A certificate of successful completion of "IATF 16949 Core Tool - Advanced Product Quality Planning (APQP)" training will be issued by the Instructor & Udemy.

Overview

Section 1: Overview of the program

Lecture 1 Overview of the program

Section 2: Fundamentals of Product Quality Planning

Lecture 2 Fundamentals of Product Quality Planning

Section 3: Phases of APQP

Lecture 3 Phases of APQP - General Understanding

Lecture 4 Phase-1: Plan and Define Program

Lecture 5 Phase-2: Product Design and Development

Lecture 6 Phase-3: Process Design and Development

Lecture 7 Phase-4: Product and Process Validation

Lecture 8 Phase-5: Feedback, Assessment and Corrective Action

Section 4: Control Plan Methodology

Lecture 9 Control Plan Format and Example

Lecture 10 Dominant Factors in Control Plan

Section 5: Product Quality Planning Checklist

Lecture 11 Product Quality Planning Checklist

Section 6: Analytical Techniques

Lecture 12 Analytical Techniques

Section 7: Summary of the program.

Lecture 13 Summary of the program.

Section 8: QUIZ on APQP

Design Engineer, Process Engineer or Engineers of other technical functions in automotive industry.,Young engineers / scientists involved in core technical activities in manufacturing industry and wants to enhance their career, with a formal added professional qualification.,Departmental Heads / Trainers who wants to provide training to their subordinates in IATF Core Tools, without sending the participants for outside training for saving of time and money.,Executive of a company can provide training to vendors of the company by casting these video training's.,An individual working as consultant in IATF 16949 field.

Iatf 16949 Core Tools - Design Fmea



Iatf 16949 Core Tools - Design Fmea
Last updated 5/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.38 GB | Duration: 2h 35m

Complete guide & EXCEL files for effective Design FMEA documentation and review.



What you'll learn
Clear understanding of various elements of DFMEA process.
Will be able to prepare and review DFMEA document effectively and coordinate with core team to improve effectiveness of design activities.
Will be able to review the DFMEA of suppliers effectively.
Will be able to analyze cause of field failures by revisiting the existing DFMEA and taking further actions.


Requirements
Person should have a degree / diploma in science / engineering / technology.
Person should have some involvement in operational function of the company such as production, quality assurance, engineering, design, testing, inspection, supplier assessment etc.
Person should be familiar with working in excel for making simple documentation, calculation, formatting etc.
An awareness of Quality Management System, such as ISO 9001, IATF 16949 would be added advantage.
Should cultivate team work in organization.
It is recommended (not essential) that the participants take the courses of IATF Core Tools - on Process flow-PFMEA-Control plan as those activities are followed after DFMEA.


Description
Designing a product is a very intricate activity. It is design which established the reliability of product. Result of design is defining the product characteristics in terms of measurable entities which would satisfy the stated and intended need of user and interested party.This course (Design FMEA) gives a systematic step by step understanding of Prerequisites, Process and After activities of Design FMEA.The specific elaboration is provided on Block / Boundary Diagram, P - Diagram, Design validation Process and Report (DVP&R).Also the AIAG FMEA 4TH EDITION is followed here for determining the rating for Severity, Occurrence and Detection.The aim of Design FMEA is to minimize the RISK associated with the design of product for its success. After taking this course one would be able to make an effective design FMEA, which would be beneficial for improvement of an existing product or introducing a new product for a design responsible organization. The course has the following sections:1. Introduction.2. Overview of FMEA Strategy, Planning and Implementation.3. Concept stage activities for DFMEA.4. Construction of Design FMEA.5. Activities after Design FMEA.6. Summary of the program.7. QUIZ on Design FMEAThis course is useful for automotive industry professionals at beginner, middle as well as senior level.

Overview
Section 1: Introduction

Lecture 1 Overview of the training programme.

Lecture 2 General FMEA Guidelines.

Section 2: Overview of FMEA Strategy, Planning and Implementation.

Lecture 3 Overview of FMEA Strategy, Planning and Implementation.

Section 3: Concept stage activities for DFMEA.

Lecture 4 Introduction to DFMEA.

Lecture 5 Prerequisites for Design FMEA.

Lecture 6 Block or Boundary Diagram.

Lecture 7 Interface Matrix.

Lecture 8 P - Diagram or Parameter Diagram.

Section 4: Construction of Design FMEA.

Lecture 9 Explanation of Design FMEA Format.

Lecture 10 Example of Design FMEA.

Section 5: Activities after Design FMEA.

Lecture 11 Activities after Design FMEA including DVP&R.

Section 6: Summary of the program.

Lecture 12 Summary of the program.

Section 7: QUIZ on Design FMEA

Design Engineer, Process Engineer or Engineers of other technical functions in a design responsible automotive industry.,Young engineers / scientists involved in core technical activities in manufacturing industry and wants to enhance their career, with a formal added professional qualification.,Departmental Heads / Trainers who wants to provide training to their subordinates in IATF Core Tools, without sending the participants for outside training for saving of time and money.,Executive of a company can provide training to vendors of the company by casting these video trainings.,An individual working as consultant in IATF 16949 field.

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Unsupervised Machine Learning Hidden Markov Models in Python (Last updated 2/2023)



Unsupervised Machine Learning Hidden Markov Models in Python (Last updated 2/2023)
Last updated 2/2023
Created by Lazy Programmer Team,Lazy Programmer Inc.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 64 Lectures ( 9h 48m ) | Size: 2 GB

HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.



What you'll learn
Understand and enumerate the various applications of Markov Models and Hidden Markov Models
Understand how Markov Models work
Write a Markov Model in code
Apply Markov Models to any sequence of data
Understand the mathematics behind Markov chains
Apply Markov models to language
Apply Markov models to website analytics
Understand how Google's PageRank works
Understand Hidden Markov Models
Write a Hidden Markov Model in Code
Write a Hidden Markov Model using Theano
Understand how gradient descent, which is normally used in deep learning, can be used for HMMs


Requirements
Familiarity with probability and statistics
Understand Gaussian mixture models
Be comfortable with Python and Numpy


Description
TheHidden Markov Model or HMMis all about learning sequences.A lot of the data that would be very useful for us to model is in sequences. Stock prices are sequences of prices. Language is a sequence of words. Credit scoring involves sequences of borrowing and repaying money, and we can use those sequences to predict whether or not you're going to default. In short, sequences are everywhere, and being able to analyze them is an important skill in your data science toolbox.The easiest way to appreciate the kind of information you get from a sequence is to consider what you are reading right now. If I had written the previous sentence backwards, it wouldn't make much sense to you, even though it contained all the same words. So order is important.While the current fad in deep learning is to use recurrent neural networks to model sequences, I want to first introduce you guys to a machine learning algorithm that has been around for several decades now - the Hidden Markov Model.This course follows directly from my first course in Unsupervised Machine Learning for Cluster Analysis, where you learned how to measure the probability distribution of a random variable. In this course, you'll learn to measure the probability distribution of a sequence of random variables. You guys know how much I love deep learning, so there is a little twist in this course. We've already covered gradient descent and you know how central it is for solving deep learning problems. I claimed that gradient descent could be used to optimize any objective function. In this course I will show you how you can use gradient descent to solve for the optimal parameters of an HMM, as an alternative to the popular expectation-maximization algorithm.We're going to do it in Theanoand Tensorflow, which arepopular librariesfor deep learning. This is also going to teach you how to work with sequences in Theano and Tensorflow, which will be very useful when we cover recurrent neural networks and LSTMs.This course is also going to go through the many practical applications of Markov models and hidden Markov models. We're going to look at a model of sickness and health, and calculate how to predict how long you'll stay sick, if you get sick. We're going to talk about how Markov models can be used to analyze how people interact with your website, and fix problem areas like high bounce rate, which could be affecting your SEO. We'll build language models that can be used to identify a writer and even generate text - imagine a machine doing your writing for you.HMMs have been very successful in natural language processingorNLP.We'll look at what is possibly the most recent and prolific application of Markov models - Google's PageRank algorithm. And finally we'll discuss even more practical applications of Markov models, including generating images, smartphone autosuggestions, and using HMMs to answer one of the most fundamental questions in biology - how is DNA, the code of life, translated into physical or behavioral attributes of an organism?All of the materials of this course can be downloaded and installed for FREE. We will do most of our work in Numpy and Matplotlib, along with a little bit of Theano. I am always available to answer your questions and help you along your data science journey.This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about"seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you wantmorethan just a superficial look at machine learning models, this course is for you.See you in class!"If you can't implement it, you don't understand it"Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratchOther courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...Suggested Prerequisites:calculuslinear algebraprobabilityBe comfortable with the multivariate Gaussian distributionPython coding: if/else, loops, lists, dicts, setsNumpy coding: matrix and vector operations, loading a CSV fileWHATORDERSHOULDITAKEYOURCOURSESIN?:Check out the lecture "Machine Learning and AIPrerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Who this course is for
Students and professionals who do data analysis, especially on sequence data
Professionals who want to optimize their website experience
Students who want to strengthen their machine learning knowledge and practical skillset
Students and professionals interested in DNA analysis and gene expression
Students and professionals interested in modeling language and generating text from a model

Homepage

Iatf 16949 Core Tools - Measurement System Analysis (Msa)



Iatf 16949 Core Tools - Measurement System Analysis (Msa)
Last updated 3/2021
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.31 GB | Duration: 6h 45m

Detailed understanding and Excel work book on Measurement System Analysis (MSA) in line with AIAG MSA Manual-4th edn.



What you'll learn
Method and techniques of Measurement System Analysis (MSA) implementation in real scenario in the organization.
Perform a managerial analysis of the MSA implementation for having an effective measurement system.
Will be able to train juniors for conducting MSA as a long term practice.
Will be able to carry out an Measurement System Analysis Study for PPAP requirement very effectively.
Will be able to use Microsoft excel templates and files to practice this core tool and integrating with PPAP (Production Part Approval Process) submission.


Requirements
Person should have a degree / diploma in science / engineering / technology.
Person should have some involvement in the inspection and testing activities in the organization.
Should be able to understand Microsoft Excel formulae, graph etc.
Should have preliminary awareness of Quality Management System.
To understand the statistical calculations clearly, it is recommended that the participant take the course of "Practicing IATF Core Tools -SPC" also.


Description
The course material is organized in sequence of several sections and sub-sections. The basic understanding is elaborated in first few sections, so that even a new comer can follow the course easily. The sections which are related to shop implementation of MSA are elaborated in details with examples in excel sheet. At the end there is a quiz which will help recaps of the key understanding of various sections. Downloadable materials are provided which are useful for technical knowledge, practicing MSA in the organization and also for PPAP submission.

Overview
Section 1: Introduction to MSA

Lecture 1 Overview of Training Program.

Section 2: General Measurement System Guideline.

Lecture 2 Introduction to MSA and Purpose.

Section 3: Terminology related to MSA.

Lecture 3 Terminology related to MSA.

Section 4: Measurement Process.

Lecture 4 Measurement Process.

Section 5: Recommended practices For Replicable Measurement System.

Lecture 5 Test Procedure

Lecture 6 Stability Study

Lecture 7 Bias Study

Lecture 8 Linearity Study

Lecture 9 Gage R&R Study Methods

Lecture 10 Gage R&R Study - Range Method

Lecture 11 Gage R&R Study - Average and Range Method

Lecture 12 Gage R&R Study - ANOVA Method

Lecture 13 Gage R&R Study - Using Minitab Software

Section 6: MSA Study - Attribute Measurement Data

Lecture 14 MSA for Attribute Measurement Data

Lecture 15 Effectiveness Parameters for Attribute Measurement Data

Lecture 16 Interrater Reliability Parameters for Attribute Measurement Data (Kappa)

Section 7: MSA for Non-Replicable Measurement Systems

Lecture 17 MSA for Non-Replicable Measurement Systems

Section 8: Summary of the program and Quiz.

Lecture 18 Summary of the program.

Persons holding executive responsibility in Quality, Manufacturing, Engineering function of automotive manufacturing industries.,Young engineers and scientists working in automotive industries or in other manufacturing industries or in a business process organization and looking for career enhancement.,Department Head / Training Head may offer this program to his / her subordinates for effective training without sending the persons outside for training.,Senior Technical Persons of the company who wants to provide internal training to the junior executives for working as a team and for making PPAP documentation.,Individual who is providing consultancy in IATF 16949-2016 implementation and audit.

Homepage

Iatf 16949 Core Tools - Process Flow - Pfmea - Control Plan



Iatf 16949 Core Tools - Process Flow - Pfmea - Control Plan
Last updated 6/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.82 GB | Duration: 3h 28m

Complete explanation of IATF Core Tools for Process Flow, Process FMEA and Control Plan and worked example.



What you'll learn
1. Method and techniques of Process Flow (PFLOW) documentation in terms of relevant information.
2. Method and techniques of Process Failure Mode and Effect Analysis (PFMEA) documentation in terms of relevant information.
3. Method and techniques of Control Plan (CPLAN) documentation in terms of relevant information.
4. Use of Microsoft excel for integration of PFLOW, PFMEA and CPLAN.


Requirements
1. Degree / Diploma in science or engineering.
2. Have a preliminary awareness of IATF 16949-2016 QMS standard (desirable).
3. Analytical and logical approach in understanding technical subject.
4. Some work experience in one or more technical functions in the company (desirable).
5. Preliminary understanding of simple product drawings, specifications, measurement methods, check sheets / technical records related to manufacturing process.
6. Preliminary working knowledge in Microsoft Excel (desirable).


Description
This course will give your in-depth understanding of IATF Core Tools (Process Flow, Process Failure Mode and Effect Analysis and Control Plan) and will take you through an example. Downloadable excel files and PDF files are provided which you can use for making these documents effectively for your organization products.

Overview
Section 1: Introduction and course overview

Lecture 1 Introduction of the trainer and the course applicability

Lecture 2 Overview of IATF Core tools (Process flow, PFMEA and Control Plan)

Section 2: Process Flow (PFLOW)

Lecture 3 PFLOW Detailed Explanation

Lecture 4 PFLOW Example

Section 3: Process Failure Mode and Effect Analysis (PFMEA)

Lecture 5 PFMEA Details Explanation

Lecture 6 PFMEA Example

Lecture 7 Reduction of Occurrence number in PFMEA - Cause Analysis

Section 4: Control Plan (CPLAN)

Lecture 8 Control Plan (CPLAN) Detailed Explanation

Lecture 9 Example of Control Plan for manufacturing

Section 5: Summary of the program.

Lecture 10 Summary of the program.

1. Persons holding executive responsibility in Quality, Manufacturing, Engineering function of automotive manufacturing industries.,2. Young engineers and scientists working in automotive industries and looking for career enhancement.,3. Department Head / Training Head may offer this program to his / her subordinates for effective training without sending the persons outside for training.,4. Senior Technical Persons of the company who wants to provide internal training to the junior executives for working as a team and for making PPAP documentation.

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IATF Core Tools - PFLOW, FMEA, CPLAN, SPC, MSA, PPAP, APQP.



IATF Core Tools - PFLOW, FMEA, CPLAN, SPC, MSA, PPAP, APQP.
Last updated 7/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 18.93 GB | Duration: 31h 37m

All Core Tools of IATF 16949: Process Flow, Process FMEA, Control Plan, Design FMEA, SPC, MSA, PPAP and APQP



What you'll learn
Clear understanding of various elements of All Core Tools of IATF 16949: 2016 QMS and processes.
Will be able to prepare and review PPAP document effectively to improve effectiveness of product design, process design and development activities.
Will be able to review the PPAP of suppliers effectively.
Will be able to formulate effective PROCESS FLOW, DFMEA, PFMEA and CONTROL PLAN for different types of processes.
Will be able to contribute in internal audit and supplier audit process effectively.
Will be able to implement SPC in the organization for quality improvement.
Will be able to conduct MSA for Variable and Attribute Measurements Effectively.
Will be able to practice APQP process effectively to meet the customer's timeline.
People from Bulk Material industries will get a clear understanding (in PPAP section) about how the core tools are applied differently for bulk materials.


Requirements
Person should have a degree / diploma in science / engineering / technology.
Person should have some involvement in operational function of the company such as production, quality assurance, engineering, design, testing, inspection, supplier assessment, purchase, service etc.
Person should be familiar with working in excel for making simple documentation, calculation, formatting etc.
An awareness of Quality Management System, such as ISO 9001, IATF 16949 would be added advantage.
Should cultivate team work in organization.


Description
This course covers the following IATF Core Tools in details, namely: 1. Process Flow Diagram,2. Process Failure Mode and Effect Analysis (PFMEA),3. Control Plan,4. Design Failure Mode and Effect Analysis (DFMEA),5. Statistical Process Control (SPC),6. Measurement System Analysis (MSA),7. Production Part Approval Process (PPAP) and8. Advanced Product Quality Planning (APQP).The course material is in line with the following AIAG Manuals:AIAG FMEA Manual - 4th edition,AIAG SPC Manual - 2nd edition,AIAG MSA Manual - 4th edition,AIAG PPAP Manual - 4th edition andAIAG APQP Manual - 2nd edition.Apart from details explanation of the various elements of Core Tools, downloadable resources are provided (in excel file) which can used in practice.Also there are quizzes in every section for testing the knowledge gained from the course.

Overview
Section 1: Introduction

Lecture 1 Overview of the program

Section 2: Process Flow, PFMEA and Control Plan

Lecture 2 Overview of Process Flow, Process FMEA and Control Plan

Lecture 3 Process Flow - Details Explanation

Lecture 4 Process Flow Example

Lecture 5 Process FMEA Detail Explanation

Lecture 6 Process FMEA example

Lecture 7 Process FMEA example of OCCURRENCE NUMBER reduction

Lecture 8 Control Plan - Details Explanation

Lecture 9 Control Plan - Example

Lecture 10 Summary of the program - PFLOW-PFMEA-CPLAN.

Section 3: Design Failure Mode and Effects Analysis (Design FMEA)

Lecture 11 General FMEA Guidelines.

Lecture 12 Overview of FMEA Strategy, Planning and Implementation.

Lecture 13 Introduction to DFMEA.

Lecture 14 Prerequisites for Design FMEA.

Lecture 15 Block or Boundary Diagram.

Lecture 16 Interface Matrix.

Lecture 17 P - Diagram or Parameter Diagram.

Lecture 18 Explanation of Design FMEA Format.

Lecture 19 Example of Design FMEA.

Lecture 20 Activities after Design FMEA.

Lecture 21 Summary of the Design FMEA Training Program.

Section 4: Statistical Process Control (SPC).

Lecture 22 Purpose of SPC in automotive manufacturing.

Lecture 23 Basic understanding of SPC.

Lecture 24 Steps for Implementation of SPC.

Lecture 25 Making X-bar/R - control chart in shop floor.

Lecture 26 Calculation of Control Limits for X-bar/R - control chart.

Lecture 27 Analysis and Correction of Control Limits for X-bar / R Control Chart.

Lecture 28 Implementation of X-bar / R Control Chart

Lecture 29 Other variable control charts.

Lecture 30 Attribute control charts.

Lecture 31 Process Capability and Process Performance.

Lecture 32 Over-adjustment.

Lecture 33 Selection of appropriate control chart.

Lecture 34 Stoplight and Pre-Control methods.

Lecture 35 Use of Minitab for SPC

Lecture 36 Summary of SPC Training.

Section 5: Measurement System Analysis (MSA).

Lecture 37 Introduction and Purpose of MSA.

Lecture 38 Terminology related to MSA.

Lecture 39 Measurement Process.

Lecture 40 Replicable Measurement System - Test Procedure.

Lecture 41 Stability Study.

Lecture 42 Bias Study.

Lecture 43 Linearity Study.

Lecture 44 Gage R&R Study Methods.

Lecture 45 Gage R&R Study - Range Method.

Lecture 46 Gage R&R Study - Average and Range Method.

Lecture 47 Gage R&R Study - ANOVA Method.

Lecture 48 Gage R&R Study by using MINITAB Software.

Lecture 49 MSA for Attribute Measurement Data.

Lecture 50 MSA for Attribute Measurement Data - Effectiveness Parameters.

Lecture 51 MSA for Attribute Measurement Data - Interraters Reliability.

Lecture 52 Non-Replicable Measurements - MSA Study.

Lecture 53 Summary MSA Training Program.

Section 6: Production Part Approval Process (PPAP)

Lecture 54 Introduction to PPAP.

Lecture 55 General understanding of Submission of PPAP.

Lecture 56 Significant Production Run.

Lecture 57 18 Elements of PPAP Document and Parts.

Lecture 58 Design Record.

Lecture 59 Authorized Engineering Change Documents.

Lecture 60 Customer Engineering Approval.

Lecture 61 Design FMEA.

Lecture 62 Process Flow Diagram.

Lecture 63 Process FMEA.

Lecture 64 Control Plan.

Lecture 65 Measurement System Analysis (MSA).

Lecture 66 Dimensional Result.

Lecture 67 Material Test Results.

Lecture 68 Performance Test Results.

Lecture 69 Initial Process Studies.

Lecture 70 Qualified Laboratory Documentation.

Lecture 71 Appearance Approval Report (AAR).

Lecture 72 Sample Production Parts.

Lecture 73 Master Sample.

Lecture 74 Checking Aids.

Lecture 75 Customer-Specific Requirements.

Lecture 76 Part Submission Warrant (PSW).

Lecture 77 Customer Notification.

Lecture 78 Submission to Customer.

Lecture 79 PPAP Submission Levels.

Lecture 80 PPAP Submission Status.

Lecture 81 Record Retention for PPAP.

Lecture 82 Bulk Material Specific Requirements Part-1.

Lecture 83 Bulk Material Specific Requirements - Part-2.

Lecture 84 Bulk Material Specific Requirements - Part-3.

Lecture 85 Tire / Tyre Industry Specific Requirements.

Lecture 86 Truck Industries Specific Requirements.

Lecture 87 Summary of PPAP Training Program.

Section 7: Advanced Product Quality Planning (APQP)

Lecture 88 Fundamentals of Product Quality Planning

Lecture 89 Phases of APQP - General Understanding

Lecture 90 Phase-1: Plan and Define Program

Lecture 91 Phase-2: Product Design and Development

Lecture 92 Phase-3: Process Design and Development

Lecture 93 Phase-4: Product and Process Validation

Lecture 94 Phase-5: Feedback, Assessment and Corrective Action

Lecture 95 Control Plan Format and Example

Lecture 96 Dominating Factors in Control Plan

Lecture 97 Product Quality Planning Checklist

Lecture 98 Analytical Techniques

Lecture 99 Summary of APQP program

Design Engineer, Process Engineer or Engineers of other technical and tecno-commercial functions in automotive industry.,Young engineers / scientists involved in technical activities in manufacturing industry and wants to enhance their career, with a formal added professional qualification.,Departmental Heads / Trainers who wants to provide training to their subordinates in IATF Core Tools, without sending the participants for outside training for saving of time and money.,Executive of a company can provide training to vendors of the company by casting these video training's.,An individual working as consultant in IATF 16949 field.

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Deep Learning Prerequisites: Logistic Regression in Python



Deep Learning Prerequisites: Logistic Regression in Python
Genre: eLearning | MP4 | Video: h264, 1278x796 | Audio: aac, 44100 Hz
Language: English + SRT | Size: 1.10 GB | Duration: 6h 19m

What you'll learn
program logistic regression from scratch in Python
describe how logistic regression is useful in data science
derive the error and update rule for logistic regression
understand how logistic regression works as an analogy for the biological neuron
use logistic regression to solve real-world business problems like predicting user actions from e-commerce data and facial expression recognition
understand why regularization is used in machine learning

Requirements
Derivatives, matrix arithmetic, probability
You should know some basic Python coding with the Numpy Stack

Description
This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python.

This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.

This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we'll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.

Another project at the end of the course shows you how you can use deep learning for facial expression recognition. Imagine being able to predict someone's emotions just based on a picture!

If you are a programmer and you want to enhance your coding abilities by learning about data science, then this course is for you. If you have a technical or mathematical background, and you want use your skills to make data-driven decisions and optimize your business using scientific principles, then this course is for you.

This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

"If you can't implement it, you don't understand it"

Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...

Suggested Prerequisites:

calculus (taking derivatives)

matrix arithmetic

probability

Python coding: if/else, loops, lists, dicts, sets

Numpy coding: matrix and vector operations, loading a CSV file

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Who this course is for:
Adult learners who want to get into the field of data science and big data
Students who are thinking of pursuing machine learning or data science
Students who are tired of boring traditional statistics and prewritten functions in R, and want to learn how things really work by implementing them in Python
People who know some machine learning but want to be able to relate it to artificial intelligence
People who are interested in bridging the gap between computational neuroscience and machine learning

Deep Learning Prerequisites: Linear Regression in Python (Update)



Deep Learning Prerequisites: Linear Regression in Python (Update)
Bestseller | h264, yuv420p, 1280x720 | ENGLISH, aac, 44100 Hz, 2 channels | 6h 10mn | 1.08 GB
Created by: Lazy Programmer Inc.

Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.



What you'll learn

Derive and solve a linear regression model, and apply it appropriately to data science problems
Program your own version of a linear regression model in Python


Requirements

How to take a derivative using calculus
Basic Python programming
For the advanced section of the course, you will need to know probability


Description

This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own linear regression module in Python.

Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you'll be returning to it for years to come. That's why it's a great introductory course if you're interested in taking your first steps in the fields of:

deep learning

machine learning

data science

statistics

In the first section, I will show you how to use 1-D linear regression to prove that Moore's Law is true.

What's that you say? Moore's Law is not linear?

You are correct! I will show you how linear regression can still be applied.

In the next section, we will extend 1-D linear regression to any-dimensional linear regression - in other words, how to create a machine learning model that can learn from multiple inputs.

We will apply multi-dimensional linear regression to predicting a patient's systolic blood pressure given their age and weight.

Finally, we will discuss some practical machine learning issues that you want to be mindful of when you perform data analysis, such as generalization, overfitting, train-test splits, and so on.

This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for FREE.

If you are a programmer and you want to enhance your coding abilities by learning about data science, then this course is for you. If you have a technical or mathematical background, and you want to know how to apply your skills as a software engineer or "hacker", this course may be useful.

This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

Suggested Prerequisites:

calculus (taking derivatives)

matrix arithmetic

probability

Python coding: if/else, loops, lists, dicts, sets

Numpy coding: matrix and vector operations, loading a CSV file

TIPS (for getting through the course):

Watch it at 2x.

Take handwritten notes. This will drastically increase your ability to retain the information.

Write down the equations. If you don't, I guarantee it will just look like gibberish.

Ask lots of questions on the discussion board. The more the better!

Realize that most exercises will take you days or weeks to complete.

Write code yourself, don't just sit there and look at my code.

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

Check out the lecture "What order should I take your courses in?" (available in the Appendix of any of my courses, including the free Numpy course)


Who this course is for:

People who are interested in data science, machine learning, statistics and artificial intelligence
People new to data science who would like an easy introduction to the topic
People who wish to advance their career by getting into one of technology's trending fields, data science
Self-taught programmers who want to improve their computer science theoretical skills
Analytics experts who want to learn the theoretical basis behind one of statistics' most-used algorithms