IATF Core Tools - PFLOW, FMEA, CPLAN, SPC, MSA, PPAP, APQP.
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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.
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/iatf-core-tools-pflow-fmea-cplan-spc-msa-ppap-apqp/
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Code:
https://k2s.cc/file/71c5d4c15fb02/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part1.rar
https://k2s.cc/file/1f9bbda7c1bd1/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part2.rar
https://k2s.cc/file/cdf94910067e0/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part3.rar
https://k2s.cc/file/8b76b2c95409d/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part4.rar
Code:
https://nitroflare.com/view/CF73E86CB81441A/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part1.rar
https://nitroflare.com/view/29D68457C6783D7/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part2.rar
https://nitroflare.com/view/EB7EF846938D702/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part3.rar
https://nitroflare.com/view/2073A2E5DE0BABE/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part4.rar
Code:
https://rapidgator.net/file/585741de05393f883b5585af66b76bdd/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part1.rar.html
https://rapidgator.net/file/0ae22a0719137ef460184d3b08d9c9a7/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part2.rar.html
https://rapidgator.net/file/814548e00c177a450212768fe129d23f/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part3.rar.html
https://rapidgator.net/file/828e5047a09893cdc13702ccd202b0fa/IATF_Core_Tools_PFLOW_FMEA_CPLAN_SPC_MSA_PPAP_APQP.part4.rar.html
Deep Learning Prerequisites: Logistic Regression in Python
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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
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Code:
https://k2s.cc/file/83f18d3e8eb52/data_science_logistic_regression_in_python.rar
Code:
https://nitroflare.com/view/7DE33D5639BF8AB/data_science_logistic_regression_in_python.rar
Code:
https://rapidgator.net/file/73c5b6365cdd33a6014c6bdf0da3a5b4/data_science_logistic_regression_in_python.rar.html
Deep Learning Prerequisites: Linear Regression in Python (Update)
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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
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitroflare.com/view/2389870D28E1468/Deep_Learning_Prerequisites_Linear_Regression_in_Python.rar
Code:
https://rapidgator.net/file/37956dfc77aaee2a5c9e034736fd8fd9/Deep_Learning_Prerequisites_Linear_Regression_in_Python.rar.html
Code:
https://k2s.cc/file/26705436c0c30/Deep_Learning_Prerequisites_Linear_Regression_in_Python.rar
Bayesian Machine Learning in Python: A/B Testing (updated 11/2022)
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Bayesian Machine Learning in Python: A/B Testing (updated 11/2022)
Last updated 11/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.59 GB | Duration: 10h 24m
Data Science, Machine Learning, and Data Analytics Techniques for Marketing, Digital Media, Online Advertising, and More
What you'll learn
Use adaptive algorithms to improve A/B testing performance
Understand the difference between Bayesian and frequentist statistics
Apply Bayesian methods to A/B testing
Requirements
Probability (joint, marginal, conditional distributions, continuous and discrete random variables, PDF, PMF, CDF)
Python coding with the Numpy stack
Description
This course is all about A/B testing.A/B testing is used everywhere. Marketing, retail, newsfeeds, online advertising, and more.A/B testing is all about comparing things.If you're a data scientist, and you want to tell the rest of the company, "logo A is better than logo B", well you can't just say that without proving it using numbers and statistics.Traditional A/B testing has been around for a long time, and it's full of approximations and confusing definitions.In this course, while we will do traditional A/B testing in order to appreciate its complexity, what we will eventually get to is the Bayesian machine learning way of doing things.First, we'll see if we can improve on traditional A/B testing with adaptive methods. These all help you solve the explore-exploit dilemma.You'll learn about the epsilon-greedy algorithm, which you may have heard about in the context of reinforcement learning.We'll improve upon the epsilon-greedy algorithm with a similar algorithm called UCB1.Finally, we'll improve on both of those by using a fully Bayesian approach.Why is the Bayesian method interesting to us in machine learning?It's an entirely different way of thinking about probability.It's a paradigm shift.You'll probably need to come back to this course several times before it fully sinks in.It's also powerful, and many machine learning experts often make statements about how they "subscribe to the Bayesian school of thought".In sum - it's going to give us a lot of powerful new tools that we can use in machine learning.The things you'll learn in this course are not only applicable to A/B testing, but rather, we're using A/B testing as a concrete example of how Bayesian techniques can be applied.You'll learn these fundamental tools of the Bayesian method - through the example of A/B testing - and then you'll be able to carry those Bayesian techniques to more advanced machine learning models in the future.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:Probability (joint, marginal, conditional distributions, continuous and discrete random variables, PDF, PMF, CDF)Python coding: if/else, loops, lists, dicts, setsNumpy, Scipy, MatplotlibWHAT 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)UNIQUE FEATURESEvery line of code explained in detail - email me any time if you disagreeNo wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratchNot afraid of university-level math - get important details about algorithms that other courses leave out
Overview
Section 1: Introduction and Outline
Lecture 1 What's this course all about?
Lecture 2 Where to get the code for this course
Lecture 3 How to succeed in this course
Section 2: The High-Level Picture
Lecture 4 Real-World Examples of A/B Testing
Lecture 5 What is Bayesian Machine Learning?
Section 3: Bayes Rule and Probability Review
Lecture 6 Review Section Introduction
Lecture 7 Probability and Bayes' Rule Review
Lecture 8 Calculating Probabilities - Practice
Lecture 9 The Gambler
Lecture 10 The Monty Hall Problem
Lecture 11 Maximum Likelihood Estimation - Bernoulli
Lecture 12 Click-Through Rates (CTR)
Lecture 13 Maximum Likelihood Estimation - Gaussian (pt 1)
Lecture 14 Maximum Likelihood Estimation - Gaussian (pt 2)
Lecture 15 CDFs and Percentiles
Lecture 16 Probability Review in Code
Lecture 17 Probability Review Section Summary
Lecture 18 Beginners: Fix Your Understanding of Statistics vs Machine Learning
Lecture 19 Suggestion Box
Section 4: Traditional A/B Testing
Lecture 20 Confidence Intervals (pt 1) - Intuition
Lecture 21 Confidence Intervals (pt 2) - Beginner Level
Lecture 22 Confidence Intervals (pt 3) - Intermediate Level
Lecture 23 Confidence Intervals (pt 4) - Intermediate Level
Lecture 24 Confidence Intervals (pt 5) - Intermediate Level
Lecture 25 Confidence Intervals Code
Lecture 26 Hypothesis Testing - Examples
Lecture 27 Statistical Significance
Lecture 28 Hypothesis Testing - The API Approach
Lecture 29 Hypothesis Testing - Accept Or Reject?
Lecture 30 Hypothesis Testing - Further Examples
Lecture 31 Z-Test Theory (pt 1)
Lecture 32 Z-Test Theory (pt 2)
Lecture 33 Z-Test Code (pt 1)
Lecture 34 Z-Test Code (pt 2)
Lecture 35 A/B Test Exercise
Lecture 36 Classical A/B Testing Section Summary
Section 5: Bayesian A/B Testing
Lecture 37 Section Introduction: The Explore-Exploit Dilemma
Lecture 38 Applications of the Explore-Exploit Dilemma
Lecture 39 Epsilon-Greedy Theory
Lecture 40 Calculating a Sample Mean (pt 1)
Lecture 41 Epsilon-Greedy Beginner's Exercise Prompt
Lecture 42 Designing Your Bandit Program
Lecture 43 Epsilon-Greedy in Code
Lecture 44 Comparing Different Epsilons
Lecture 45 Optimistic Initial Values Theory
Lecture 46 Optimistic Initial Values Beginner's Exercise Prompt
Lecture 47 Optimistic Initial Values Code
Lecture 48 UCB1 Theory
Lecture 49 UCB1 Beginner's Exercise Prompt
Lecture 50 UCB1 Code
Lecture 51 Bayesian Bandits / Thompson Sampling Theory (pt 1)
Lecture 52 Bayesian Bandits / Thompson Sampling Theory (pt 2)
Lecture 53 Thompson Sampling Beginner's Exercise Prompt
Lecture 54 Thompson Sampling Code
Lecture 55 Thompson Sampling With Gaussian Reward Theory
Lecture 56 Thompson Sampling With Gaussian Reward Code
Lecture 57 Exercise on Gaussian Rewards
Lecture 58 Why don't we just use a library?
Lecture 59 Nonstationary Bandits
Lecture 60 Bandit Summary, Real Data, and Online Learning
Lecture 61 (Optional) Alternative Bandit Designs
Section 6: Bayesian A/B Testing Extension
Lecture 62 More about the Explore-Exploit Dilemma
Lecture 63 Confidence Interval Approximation vs. Beta Posterior
Lecture 64 Adaptive Ad Server Exercise
Section 7: Practice Makes Perfect
Lecture 65 Intro to Exercises on Conjugate Priors
Lecture 66 Exercise: Die Roll
Lecture 67 The most important quiz of all - Obtaining an infinite amount of practice
Section 8: Setting Up Your Environment (FAQ by Student Request)
Lecture 68 Anaconda Environment Setup
Lecture 69 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
Section 9: Extra Help With Python Coding for Beginners (FAQ by Student Request)
Lecture 70 How to Code by Yourself (part 1)
Lecture 71 How to Code by Yourself (part 2)
Lecture 72 Proof that using Jupyter Notebook is the same as not using it
Lecture 73 Python 2 vs Python 3
Section 10: Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Lecture 74 How to Succeed in this Course (Long Version)
Lecture 75 Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
Lecture 76 Machine Learning and AI Prerequisite Roadmap (pt 1)
Lecture 77 Machine Learning and AI Prerequisite Roadmap (pt 2)
Section 11: Appendix / FAQ Finale
Lecture 78 What is the Appendix?
Lecture 79 BONUS
Students and professionals with a technical background who want to learn Bayesian machine learning techniques to apply to their data science work
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/bayesian-machine-learning-in-python-ab-testing/
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Code:
https://k2s.cc/file/e83a2d8ad5db0/Bayesian_Machine_Learning_in_Python_AB_Testing.rar
Code:
https://nitroflare.com/view/BFB7B0B19ADAC96/Bayesian_Machine_Learning_in_Python_AB_Testing.rar
Code:
https://rapidgator.net/file/4823f1842803af0ab991d787d00f137c/Bayesian_Machine_Learning_in_Python_AB_Testing.rar.html
SAP Ariba Simplified Procurement & Supply Chain Solutions 2022
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SAP Ariba Simplified Procurement & Supply Chain Solutions 2022
Published 07/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 8.47 GB | Duration: 112 lectures • 35h 42m
Complete SAP Ariba End To End Implementation Training Courses
What you'll learn
Configuration and Implementation for SAP Ariba module
Requirements gathering for the Business Record to Report process cycle
After Completing this course, you will become SAP Ariba Consultant with understanding of logic behind configuration
Hands-on experience with SAP Ariba
Requirements
Mobile
PC Or Laptop
Description
Why choose SAP Ariba?
Influence what happens next for your organization. Digitalize and fully integrate your source-to-pay process with market-leading spend management solutions for sourcing and procurement. You'll get the data-drive intelligence and supply chain visibility you need to mitigate supplier risk and achieve long-term resiliency against supply chain disruption. And working within the connected community of the world's largest business network, engage in real-time supplier collaboration and dynamic partnerships to drive innovation and keep your business moving forward.
What is SAP Ariba?
SAP Ariba is a cloud-based innovative solution that allows suppliers and buyers to connect and do business on a single platform. It improves over all vendor management system of an organization by providing less costly ways of procurement and making business simple. Ariba acts as supply chain, procurement service to do business globally. SAP Ariba digitally transforms your supply chain, procurement and contract management process.
In today's world, there is a need to control your supply chain and to collaborate with your suppliers in an efficient way. To enable healthy supply chain, you need to have suppliers with visibility to every part of procurement process so that they can maintain an efficient supply chain and help organizations to grow their and own business.
The cloud based innovative solution was first developed in 1996 by a company named Ariba and was later acquired by SAP in 2012 with a total acquisition cost of 4.3 billion USD with each share cost $45. Thus, the name SAP Ariba. At the onset, Ariba was a B2B company to do procurement over Internet and was the first one to introduce IPO in 1999.
Key Features of SAP Ariba
In this section, we will learn about the key features of SAP Ariba.
SAP Ariba is a B2B solution that allows you to connect to the world's largest network of vendors and suppliers and enhance business collaboration with the right business partners.
SAP Ariba allows organizations to connect with the right suppliers with deep visibility to your inside vendor and procurement management processes giving way to error free business transactions.
With SAP Ariba, you can directly connect Ariba network with millions of suppliers meeting your business needs and managing supply chain.
SAP Ariba network removes overall complexity in procurement process and suppliers and buyers can manage all key terms of vendor management on a single network.
With acquisition of SAP, Ariba can easily integrate with different SAP ERP solutions like SAP ECC and S/4 HANA with easy to configure workflows to automate different processes in complete procurement cycle.
You can easily integrate master and transactional data from different ERP solution to Ariba processes.
Who this course is for
SAP Ariba Consultant
SAP Ariba Developer
SAP Ariba End-User
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/sap-ariba-simplified-procurement-supply-chain-solutions-2022/
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Code:
https://nitroflare.com/view/D4F199F77A1C362/SAP_Ariba_Simplified_Procurement_%26_Supply_Chain_Solutions.part1.rar
https://nitroflare.com/view/494AA39CCD61ACC/SAP_Ariba_Simplified_Procurement_%26_Supply_Chain_Solutions.part2.rar
Code:
https://k2s.cc/file/ee593d5674d1d/SAP_Ariba_Simplified_Procurement___Supply_Chain_Solutions.part1.rar
https://k2s.cc/file/e378215763bc7/SAP_Ariba_Simplified_Procurement___Supply_Chain_Solutions.part2.rar
Code:
https://rapidgator.net/file/5b44832478d6c4f2aa17dabf03059d22/SAP_Ariba_Simplified_Procurement_&_Supply_Chain_Solutions.part1.rar.html
https://rapidgator.net/file/18f6b1f9fca8cddb1bfc51f8255fb650/SAP_Ariba_Simplified_Procurement_&_Supply_Chain_Solutions.part2.rar.html
Data Science & Machine Learning Naive Bayes in Python
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Data Science & Machine Learning Naive Bayes in Python
Published 11/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 32 lectures (5h) | Size: 2.2 GB
Master a crucial artificial intelligence algorithm and skyrocket your Python programming skills
What you'll learn
Apply Naive Bayes to image classification (Computer Vision)
Apply Naive Bayes to text classification (NLP)
Apply Naive Bayes to Disease Prediction, Genomics, and Financial Analysis
Understand Naive Bayes concepts and algorithm
Implement multiple Naive Bayes models from scratch
Requirements
Decent Python programming skills
Experience with Numpy, Matplotlib, and Pandas (we'll be using these)
For advanced portions: know probability
Description
In this self-paced course, you will learn how to apply Naive Bayes to many real-world datasets in a wide variety of areas, such as
computer vision
natural language processing
financial analysis
healthcare
genomics
Why should you take this course? Naive Bayes is one of the fundamental algorithms in machine learning, data science, and artificial intelligence. No practitioner is complete without mastering it.
This course is designed to be appropriate for all levels of students, whether you are beginner, intermediate, or advanced. You'll learn both the intuition for how Naive Bayes works and how to apply it effectively while accounting for the unique characteristics of the Naive Bayes algorithm. You'll learn about when and why to use the different versions of Naive Bayes included in Scikit-Learn, including GaussianNB, BernoulliNB, and MultinomialNB.
In the advanced section of the course, you will learn about how Naive Bayes really works under the hood. You will also learn how to implement several variants of Naive Bayes from scratch, including Gaussian Naive Bayes, Bernoulli Naive Bayes, and Multinomial Naive Bayes. The advanced section will require knowledge of probability, so be prepared!
Thank you for reading and I hope to see you soon!
Suggested Prerequisites
Decent Python programming skill
Comfortable with data science libraries like Numpy and Matplotlib
For the advanced section, probability knowledge is required
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 my free course)
UNIQUE FEATURES
Every line of code explained in detail - email me any time if you disagree
Less than 24 hour response time on Q&A on average
Not afraid of university-level math - get important details about algorithms that other courses leave out
Who this course is for
Beginner Python developers curious about data science and machine learning
Students and professionals interested in machine learning fundamentals
Homepage
Code:
https://anonymz.com/?https://www.udemy.com/course/data-science-machine-learning-naive-bayes-in-python/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://nitroflare.com/view/428C6061C88F69A/Data_Science_%26_Machine_Learning_Naive_Bayes_in_Python.rar
Code:
https://k2s.cc/file/540d2b156db2a/Data_Science___Machine_Learning_Naive_Bayes_in_Python.rar
Code:
https://rapidgator.net/file/e0a875882e6a4e38448e04ce0f894077/Data_Science_&_Machine_Learning_Naive_Bayes_in_Python.rar.html
CBTNuggets - Windows Server Hybrid Administrator Associate Certification Training
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CBTNuggets - Windows Server Hybrid Administrator Associate Certification Training (AZ-800 & AZ-801)
Released 08/2022
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 354 Lessons (56h 11m) | Size: 52.2 GB
This intermediate-level Server Hybrid Administrator Associate training prepares systems administrators to take the AZ-800 and AZ-801 exams, which are the two exams required to earn the Windows Server Hybrid Administrator Associate certification
The AZ-800 is the first half of Microsoft's overall Windows Server Hybrid Administrator Associate. The AZ-800 is the exam someone should take if they're focused on administering servers and workloads that run on Windows Server, whether on-premises or in hybrid environments.
Even for an administrator who isn't planning on earning the whole certification, the AZ-800 is a good intermediate-level exam for testing familiarity with managing operations on Windows Servers - on-prem or hybrid.
For IT managers, this Microsoft training can be used for AZ-800 and AZ-801 exam prep, onboarding new systems administrators, individual or team training plans, or as a Microsoft reference resource.
Windows Server Hybrid Administrator Associate: What You Need to Know
This Windows Server Hybrid Administrator Associate training maps to the AZ-800 and AZ-801 exam objectives, and covers topics such as
Deploying and managing Active Directory Domain services in hybrid environments
Managing Windows Server servers and workloads in hybrid environments
Managing virtual machines and containers
Implementing and managing network infrastructure in hybrid and on-prem environments
Managing storage and file services
Who Should Take Windows Server Hybrid Administrator Associate Training?
This Windows Server Hybrid Administrator Associate training is considered associate-level Microsoft training, which means it was designed for systems administrators. This Windows Server skills course is valuable for new IT professionals with at least a year of experience with server administration tools and experienced systems administrators looking to validate their Microsoft skills.
New or aspiring systems administrators. If you're a brand new systems administrator, the AZ-800 is an essential step to earning the Windows Server Hybrid Administrator Associate - a truly excellent choice for your first certification in administration. Preparing for and passing the AZ-800 will teach you all the basics of managing hybrid network environments, which will prove fundamental to the rest of your career.
Experienced systems administrators. If you've already been working as a systems administrator for several years, passing the AZ-800 probably won't be very challenging so long as you're familiar with AD DS, hybrid workloads and virtual machines. This Windows Server Hybrid Administrator Associate training is a way to advance your career in server administration by helping you pass the AZ-800 and help you prove that you know your way around integrating Windows Server environments with Azure services.
Homepage
Code:
https://anonymz.com/?https://www.cbtnuggets.com/it-training/microsoft-azure/windows-server-hybrid-admin-associate
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://k2s.cc/file/e6bc4d9aa74ed/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part01.rar
https://k2s.cc/file/615472ef9a18f/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part02.rar
https://k2s.cc/file/dd3756ae2bf75/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part03.rar
https://k2s.cc/file/ed075b2ab432c/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part04.rar
https://k2s.cc/file/fef9db927319c/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part05.rar
https://k2s.cc/file/476bdbdbd518b/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part06.rar
https://k2s.cc/file/45672213a1a4d/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part07.rar
https://k2s.cc/file/5c3f0132412bd/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part08.rar
https://k2s.cc/file/21d4b2b6686e5/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part09.rar
https://k2s.cc/file/2715bb350f863/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part10.rar
https://k2s.cc/file/a033603882756/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800___AZ-801).part11.rar
Code:
https://nitroflare.com/view/4ADF86EE13A13F0/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part01.rar
https://nitroflare.com/view/754D89A630DF133/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part02.rar
https://nitroflare.com/view/0CAE11A24629087/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part03.rar
https://nitroflare.com/view/13AA15E654C5115/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part04.rar
https://nitroflare.com/view/B72517BAB70A368/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part05.rar
https://nitroflare.com/view/2DF5C4B9F745FF0/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part06.rar
https://nitroflare.com/view/3E408AA30D5DF12/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part07.rar
https://nitroflare.com/view/F2C9660E1225D18/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part08.rar
https://nitroflare.com/view/0A03AADA8BEAE74/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part09.rar
https://nitroflare.com/view/84B634A58C9CC11/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part10.rar
https://nitroflare.com/view/6A5C5F3861CE0E8/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_%26_AZ-801).part11.rar
Code:
https://rapidgator.net/file/aebaab4b1291f430f80b8ac0a9124526/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part01.rar.html
https://rapidgator.net/file/339e5ebd8cf4eec78c56787d6e020d0f/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part02.rar.html
https://rapidgator.net/file/bfc75c0b6190dc5feeb6a00513089661/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part03.rar.html
https://rapidgator.net/file/76241a0a67733f4d361c4bdc65e7e16b/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part04.rar.html
https://rapidgator.net/file/b586fa9c382bca2c471ad388cf7dc43a/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part05.rar.html
https://rapidgator.net/file/182c1642bdd00d478a7d44328349cc11/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part06.rar.html
https://rapidgator.net/file/d0b91e51909f41162b609452a7dc9e24/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part07.rar.html
https://rapidgator.net/file/30920418c8270c1a13ce7ad216de94f1/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part08.rar.html
https://rapidgator.net/file/d74c53ca8d2cc48c1e9c441e2658511a/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part09.rar.html
https://rapidgator.net/file/d07eb5a7ba1c889651f4bc5629340edd/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part10.rar.html
https://rapidgator.net/file/94be2e6d803a378f9fac7ea174f6c77e/Windows_Server_Hybrid_Administrator_Associate_Certification_Training_(AZ-800_&_AZ-801).part11.rar.html
Juniper JNCIA - Junos JN0-104 with 7 hours of Extra Content
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Juniper JNCIA - Junos JN0-104 with 7 hours of Extra Content
Published 08/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 109 lectures (24h 48m) | Size: 9.35 GB
Pass your Juniper JNCIA Junos JN0-104 with added Extras BGP, ISIS, OSPF and Layer 2 Protocols on vMX, QFX, SRX devices
What you'll learn
An understanding of the Juniper Junos OS and how it fits into modern networking with both enterprise and service provider environments, JNCIA JN0-104 success
How networking is the same across multiple vendors, once you know a protocol or concept you will see how easy it is to transfer your learned skills to Junos
You will be confident in dealing with Juniper equipment in your work place and stand out from the others who can't or won't
you will see Extra content from the JNCIS-ENT and the JNCIS-SP like BGP, OSPF, ISIS, and Layer 2 so you can succeed in further studies or at the work place
A good foundation into the Juniper JNCIS Enterprise and JNCIS Service Provider , Bring these skills to the workplace
Advanced Juniper JNCIS topics not included in any other JNCIA course, see how Cisco and Juniper can work well with each other
JNCIA certification will open doors at work and is the cornerstone of Juniper certification, progress from the JNCIA to the JNCIS and higher
Requirements
A basic level of networking would be great but it is not required as you will learn everything needed to pass your Juniper JNCIA JN0-104 exam but most important to progress at work or in your other networking studies
Access to either Juniper Vlabs which is free, GNS3 or EVE-NG to pratice would be of benefit however it's not required
Description
This Juniper JNCIA JN0-104 course is my first outing into video training - please be gentle on me, I have designed this course to cover all the topics on the JNCIA and I have included the PowerPoint presentations that I use.
I have included 7 hours of EXTRA content found on the Juniper JNCIS-ENT and Juniper JNCIS-SP covering basic juniper Vlans, juniper switching, juniper BGP and OSPF as well as ISIS and RIP mainly because when i done the Juniper JNCIA I was lucky that I was working with Juniper devices in a service provider environment so I was familiar with layer 2 and routing protocols but the JNCIA Junos JN0-104 does not provide this information.
Juniper certification is rewarding and a very intresting take on networking and after following my Juniper JNCIA junos jn0-104 certification course you will be ready to move on to Juniper JNCIS.
In the work place you will be able to show that you know how to monitor and configure the likes of Spanning Tree, BGP and OSPF, ISIS, RIP and more.
I believe that this course will cover two things, it will provide a solid level of knowledge if you do intend to progress to the Juniper JNCIS and it will allow you to have confidence going into your work place by being able to demonstrate that you can preform configuration on and monitor a live production network.
We will look at configuration on devices like the Juniper SRX Firewall , Juniper vMX Router and the Juniper QXF Switch
Who this course is for
Network Engineers of all levels that want to learn Juniper Junos. this course is the foundation for your further studies
Engineers that want to further their study into the Juniper JNCIS -SP or JNCIS -ENT as the Extra content will be a great help
network engineers who want to complete the JNCIA certification program and learn the fantastic Junos OS
Code:
https://anonymz.com/?https://www.udemy.com/course/juniper-jncia-junos-jn0-104-with-7-hours-of-bonus-content/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://rapidgator.net/file/9a76ddf0d19e7a147eb342dd8a87f96f/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part1.rar
https://rapidgator.net/file/cb4176ef941cea3dd43ce4ea05b8a626/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part2.rar
Code:
https://k2s.cc/file/aa7d9ad4315b8/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part1.rar
https://k2s.cc/file/509a8c49f7791/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part2.rar
Code:
https://nitroflare.com/view/FFE30D130FAB88B/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part1.rar
https://nitroflare.com/view/A0501B5CDD70F40/Juniper_JNCIA_-_Junos_JN0-104_with_7_hours_of_Extra_Content.part2.rar
Learn Advanced Modern C++
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Learn Advanced Modern C++
Last updated 7/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 7.67 GB | Duration: 24h 2m
Take your knowledge of C++ to the next level!
What you'll learn
Know and understand all the important features of modern C++
Acquire a good knowledge of the Standard Template Library
Obtain a thorough grounding in the C++ programming language
Be familiar with idiomatic uses of modern C++
Requirements
Some knowledge of C++ beyond beginner level
A compiler which supports C++11, preferably C++14 or C++17
Proficiency in English (B2 level, preferably C1)
Description
This course will enhance your knowledge of the technically challenging but powerful and efficient C++ programming language.It is designed to give you an intermediate-to-advanced level understanding of the language. There is extensive coverage of the Standard Template Library, including standard algorithm functions. Finally, a project in which you will exercise your new skills by writing a simple game.After successfully completing this course, you should be able to apply for jobs and courses which require a good knowledge of C++.The material is based around the modern version of the language. I teach the C++11, C++14 and C++17 standards, but also cover older variations which are still widely used.The course is thorough and goes into the material in depth. It assumes basic C++ knowledge, such as the material in my course "Begin Programming with Modern C++": function calls, loops, conditionals and classes.There are downloadable exercises for each video, with solutions, so you can check your understanding as you learn, gaining familiarity and confidence with the material. I will be actively supporting the course and I will respond promptly if you have any questions or experience difficulties with the course content. Please feel free to use the Q&A feature or alternatively you can send me a private message.
Overview
Section 1: Introduction
Lecture 1 Introduction to the Course
Lecture 2 Lecturer Introduction
Lecture 3 Source Code for this Course
Section 2: Review of C++
Lecture 4 Local Variables and Function Arguments
Lecture 5 Reference and Value Semantics
Lecture 6 Declaration and Initialization
Lecture 7 Classes
Lecture 8 Special Member Functions
Lecture 9 Pointers and Memory
Lecture 10 Array, String and Vector
Lecture 11 Conway's Game of Life Overview
Lecture 12 Two-Dimensional Arrays
Lecture 13 Conway's Game of Life Practical
Lecture 14 Conway's Game of Life Practical Continued
Lecture 15 Numeric Types and Literals
Lecture 16 String Literals
Lecture 17 Casting
Lecture 18 Iterator Introduction
Lecture 19 The auto keyword
Lecture 20 Loops and Iterators
Lecture 21 Iterator Arithmetic and Iterator Ranges
Lecture 22 If Statements and Switch in C++17
Lecture 23 Templates Overview
Lecture 24 Namespaces
Lecture 25 Function Pointer
Section 3: C++ String Interface
Lecture 26 Basic String Operations
Lecture 27 Searching Strings
Lecture 28 Adding Elements to Strings
Lecture 29 Removing Elements from Strings
Lecture 30 Converting between Strings and Numbers
Lecture 31 Miscellaneous String Operations
Lecture 32 Character Functions
Section 4: Files and Streams
Lecture 33 Files and Streams
Lecture 34 File Streams
Lecture 35 Streams and Buffering
Lecture 36 Unbuffered Input and Output
Lecture 37 File Modes
Lecture 38 Stream Member Functions and State
Lecture 39 Stream Manipulators and Formatting
Lecture 40 Floating-point Output Formats
Lecture 41 Stringstreams
Lecture 42 Resource Management
Lecture 43 Random Access to Streams
Lecture 44 Stream Iterators
Lecture 45 Binary Files
Lecture 46 Binary File Practical
Section 5: Special Member Functions and Operator Overloading
Lecture 47 Constructors in Modern C++
Lecture 48 Copy Constructor Overview
Lecture 49 Assignment Operator Overview
Lecture 50 Synthesized Member Functions
Lecture 51 Shallow and Deep Copying
Lecture 52 Copy Elision
Lecture 53 Conversion Operators
Lecture 54 Default and Delete Keywords
Lecture 55 Operators and Overloading.
Lecture 56 Which Operators to Overload
Lecture 57 The Friend Keyword
Lecture 58 Member and Non-member Operators
Lecture 59 Addition Operators
Lecture 60 Equality and Inequality Operators
Lecture 61 Less-than Operator
Lecture 62 Prefix and Postfix Operators
Lecture 63 Function Call Operator
Lecture 64 Printing Out Class Member Data
Section 6: Algorithms Introduction and Lambda Expressions
Lecture 65 Algorithms Overview
Lecture 66 Algorithms with Predicates
Lecture 67 Algorithms with _if Versions
Lecture 68 Lambda Expressions Introduction
Lecture 69 Lambda Expressions Practical
Lecture 70 Lambda Expressions and Capture
Lecture 71 Lambda Expressions and Capture Continued
Lecture 72 Lambda Expressions and Partial Evaluation
Lecture 73 Lambda Expressions in C++14
Lecture 74 Pair Type
Lecture 75 Insert Iterators
Lecture 76 Library Function Objects
Section 7: Algorithms Continued
Lecture 77 Searching Algorithms
Lecture 78 Searching Algorithms Continued
Lecture 79 Numeric Algorithms
Lecture 80 Write-only Algorithms
Lecture 81 for_each Algorithm
Lecture 82 Copying Algorithms
Lecture 83 Write Algorithms
Lecture 84 Removing Algorithms
Lecture 85 Removing Algorithms Continued
Lecture 86 Transform Algorithm
Lecture 87 Merging Algorithms
Lecture 88 Reordering Algorithms
Lecture 89 Partitioning Algorithms
Lecture 90 Sorting Algorithms
Lecture 91 Sorting Algorithms Continued
Lecture 92 Permutation Algorithms
Lecture 93 Min and Max Algorithms
Lecture 94 Further Numeric Algorithms
Lecture 95 Further Numeric Algorithms Continued
Lecture 96 Introduction to Random Numbers
Lecture 97 Random Numbers in Older C++
Lecture 98 Random Numbers in Modern C++
Lecture 99 Random Number Algorithms
Lecture 100 Palindrome Checker Practical
Lecture 101 Random Walk Practical
Section 8: Containers
Lecture 102 Container Introduction
Lecture 103 Standard Library Array
Lecture 104 Forward List
Lecture 105 List
Lecture 106 List Operations
Lecture 107 Deque
Lecture 108 Tree Data Structure
Lecture 109 Sets
Lecture 110 Map
Lecture 111 Maps and Insertion
Lecture 112 Maps in C++17
Lecture 113 Multiset and Multimap
Lecture 114 Searching Multimaps
Lecture 115 Unordered Associative Containers
Lecture 116 Unordered Associative Containers Continued
Lecture 117 Associative Containers and Custom Types
Lecture 118 Nested Maps
Lecture 119 Queues
Lecture 120 Priority Queues
Lecture 121 Stack
Lecture 122 Emplacement
Lecture 123 Mastermind Game Practical
Lecture 124 Containers Workshop
Section 9: Inheritance and Polymorphism
Lecture 125 Class Hierarchies and Inheritance
Lecture 126 Base and Derived Classes
Lecture 127 Member Functions and Inheritance
Lecture 128 Overloading Member Functions
Lecture 129 Pointers, References and Inheritance
Lecture 130 Static and Dynamic Type
Lecture 131 Virtual Functions
Lecture 132 Virtual Functions in C++11
Lecture 133 Virtual Destructor
Lecture 134 Interfaces and Virtual Functions
Lecture 135 Virtual Function Implementation
Lecture 136 Polymorphism
Section 10: Error Handling and Exceptions
Lecture 137 Error Handling
Lecture 138 Error codes and Exceptions
Lecture 139 Exceptions Introduction
Lecture 140 Try and Catch Blocks
Lecture 141 Catch-all Handlers
Lecture 142 Exception Mechanism
Lecture 143 std::exception Hierarchy
Lecture 144 Standard Exception Subclasses
Lecture 145 Exceptions and Special Member Functions
Lecture 146 Custom Exception Class
Lecture 147 Exception Safety
Lecture 148 The throw() Exception Specifier
Lecture 149 The noexcept keyword
Lecture 150 Swap Function
Lecture 151 Exception-safe Class
Lecture 152 Copy and Swap
Lecture 153 Comparison with Java and C# Exceptions
Section 11: Move Semantics
Lecture 154 Move Semantics
Lecture 155 Lvalues and Rvalues
Lecture 156 Lvalue and Rvalue References
Lecture 157 Value Categories
Lecture 158 Move Operators
Lecture 159 RAII Class with Move Operators
Lecture 160 Move-only Types and RAII
Lecture 161 Special Member Functions in C++11
Lecture 162 Using Special Member Functions in C++11
Lecture 163 Function Arguments and Move Semantics
Lecture 164 Forwarding References
Lecture 165 Perfect Forwarding
Lecture 166 Perfect Forwarding Practical
Lecture 167 Move Semantics Workshop
Section 12: Smart Pointers
Lecture 168 Smart Pointers Introduction
Lecture 169 Unique Pointer
Lecture 170 Unique Pointers and Polymorphism
Lecture 171 Unique Pointers and Custom Deleters
Lecture 172 The Handle-Body Pattern
Lecture 173 The pImpl Idiom
Lecture 174 Reference Counting
Lecture 175 Shared pointer
Lecture 176 Weak Pointer
Lecture 177 Weak Pointer and Cycle Prevention
Section 13: Miscellaneous Features
Lecture 178 Chrono Library Introduction
Lecture 179 Chrono Duration Types
Lecture 180 Chrono Clocks and Time Points
Lecture 181 Bitsets
Lecture 182 Tuples
Lecture 183 Tuples in C++17
Lecture 184 Unions
Lecture 185 Unions Continued
Lecture 186 Mathematical Types
Lecture 187 Bind
Lecture 188 Callable Objects
Lecture 189 Member Function Pointers
Lecture 190 Interfacing to C
Lecture 191 Run-time Type Information
Lecture 192 Multiple Inheritance
Lecture 193 Virtual Inheritance
Lecture 194 Inline Namespaces
Lecture 195 Attributes
Section 14: Compile-time Programming
Lecture 196 Compile-time Programming Overview
Lecture 197 Constant Expressions
Lecture 198 Constexpr Functions
Lecture 199 Classes and Templates
Lecture 200 Template Specialization
Lecture 201 Extern Templates
Lecture 202 Variadic Templates
Lecture 203 Miscellaneous Template Features
Lecture 204 Library-defined Operators
Lecture 205 Constexpr If Statement
Lecture 206 Constexpr If Examples
Lecture 207 The decltype Keyword
Section 15: Project: A Breakout Game Using Modern C++ with SFML
Lecture 208 Project Breakout
Lecture 209 SFML Introduction
Lecture 210 Compiler Configuration for SFML
Lecture 211 Basic Window
Lecture 212 Random Walk Revisited
Lecture 213 Sprite
Lecture 214 Ball
Lecture 215 Bouncing Ball
Lecture 216 Paddle
Lecture 217 Moving Paddle
Lecture 218 Ball-Paddle Interaction
Lecture 219 Bricks
Lecture 220 Ball Interaction with Bricks
Lecture 221 Game Manager
Lecture 222 Entity Manager Overview
Lecture 223 Entity Manager and Object Creation
Lecture 224 Entity Manager and Object Operations
Lecture 225 Brick Strength
Lecture 226 More Features
Lecture 227 Conclusion
Section 16: Resources
Lecture 228 Recommended Books
Lecture 229 C++ "Cheat Sheet" Infographics
Lecture 230 The "Awesome C++ Frameworks and Libraries" Github
Lecture 231 The "Awesome Modern C++ Resources" Github
Programmers who have some knowledge of Intermediate C++ and want to learn more,C++ developers who wish to refresh and/or update their skills
Code:
https://anonymz.com/?https://www.udemy.com/course/learn-intermediate-modern-c/
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Code:
https://rapidgator.net/file/52b45cc261c6a6d8f728bbc34fc4ec90/Learn_Advanced_Modern_C.part1.rar
https://rapidgator.net/file/bdda646d9b20ff534a8f9aa8cd0dcc6c/Learn_Advanced_Modern_C.part2.rar
Code:
https://k2s.cc/file/d3457227c3d86/Learn_Advanced_Modern_C.part1.rar
https://k2s.cc/file/de613f1e36946/Learn_Advanced_Modern_C.part2.rar
Code:
https://nitroflare.com/view/7A04AAF795F0494/Learn_Advanced_Modern_C.part1.rar
https://nitroflare.com/view/0B475F11B555143/Learn_Advanced_Modern_C.part2.rar
Check Point Firewalls Troubleshooting Expert Course (CCTE)
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Check Point Firewalls Troubleshooting Expert Course (CCTE)
Last Updated 05/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 39 lectures (13h 31m) | Size: 6.54 GB
Learn Check Point Firewall Core Concepts
What you'll learn
Check Point Firewall Advanced Concepts and Troubleshooting - VPNs , Check Point Process, Check Point Core Concepts like CoreXL and SecureXL , Connection Tables
Course is design in simple terms so easy to understand, Student can learn Concepts withing scope of timeline.
Course is mainly focus on Core Concepts of Check Point Firewalls and Troubleshooting Core Features
Student will learn and walk through various scenarios and use case while learning Course contents
Requirements
• General knowledge of TCP/IP
• Working knowledge of Windows and/or UNIX
• Working knowledge of networking technology
• Working knowledge of the Internet
Description
The following course Check Point Firewalls Troubleshooting Experts Course includes lectures on how Check Point advanced study concepts and Features work and the walk-through of the configuration in the lab/production environment. From the very beginning following step-by-step approach you will be able to grasp advanced concepts and step on the next level. The course is structured in an easy to follow manner starting from the very basic to advanced topics. The topics that are covered are: Installing Check Point in a lab environment, understanding general principles of Firewalling.
You will Learn : CLI Tools, Configuring NAT, Identity Awareness Site-to-Site VPN Between Corporate and Branch Office, VPN Troubleshooting Advanced Firewall, Advanced Clustering and Acceleration, Advanced User Management, Advanced IPsec VPN and Remote Access, Core Elements of Firewall Administration, Core Processes, User mode Process Debugs, Kernel mode process Debugs, relationship between User mode and Kernel mode process, Check Point MDS and VSX and VS configurations-Troubleshooting and Upgrade. Advanced and New Concepts of Check Point Firewall Maestro and Virtualization and Much More..
I have applied the streamlined, step-by-step method to excel as a Check Point professional in less time than you ever thought possible. I'm going to walk you through the main challenges, so you can step on the next level.
Who this course is for
System Administrators
Information Security Analysts
Support Analysts
Network Engineers
Firewall Enthusiasts
Security Engineers
Requirements
General knowledge of TCP/IP
Working knowledge of Windows and/or UNIX
Working knowledge of networking technology
Working knowledge of the Internet
CCSA basic concepts
Introductory product information is provided in video guided instruction and labs, and the more advanced, technical training is instructor-led classroom based.
Who this course is for
• System Administrators
• Information Security Analysts
• Support Analysts
• Network Engineers
• Firewall Enthusiasts
Security Engineers
Code:
https://anonymz.com/?https://www.udemy.com/course/check-point-firewalls-troubleshooting-expert-course-ccte/
[Only registered and activated users can see links. Click Here To Register...]
Code:
https://rapidgator.net/file/26d3d4c458ca1b71057f1ba72a77adb3/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part1.rar
https://rapidgator.net/file/bcef37571096498cca5c242b4dbae81a/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part2.rar
Code:
https://k2s.cc/file/aa45051b183a0/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part1.rar
https://k2s.cc/file/699ae46f6a0df/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part2.rar
Code:
https://nitroflare.com/view/A2574A4D576BFC0/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part1.rar
https://nitroflare.com/view/26233958502C00E/Check_Point_Firewalls_Troubleshooting_Expert_Course_CCTE.part2.rar