Solve Real World Business Problems with AI Solutions implemented in Python. Code templates included.
What you'll learn
OPTIMIZE BUSINESS PROCESSES
Master the General AI Framework
Implement Q-Learning
Save and Load a model
Build an Optimization Model
Implement Early Stopping
Maximize Efficiency
MAXIMIZE REVENUES
MINIMIZE COSTS
Implement Thompson Sampling
Implement Deep Q-Learning
Leverage AI to make the best decision
Build an AI Environment from scratch
Implement Online Learning
Build an Artificial Brain
Implement Regret Analysis
Requirements
High School Maths
Basic Python Knowledge
Description
Structure of the course:Part 1 - Optimizing Business ProcessesCase Study: Optimizing the Flows in an E-Commerce WarehouseAI Solution: Q-LearningPart 2 - Minimizing CostsCase Study: Minimizing the Costs in Energy Consumption of a Data CenterAI Solution: Deep Q-LearningPart 3 - Maximizing RevenuesCase Study: Maximizing Revenue of an Online Retail BusinessAI Solution: Thompson SamplingReal World Business Applications:With Artificial Intelligence, you can do three main things for any business:Optimize Business ProcessesMinimize CostsMaximize RevenuesWe will show you exactly how to succeed these applications, through Real World Business case studies. And for each of these applications we will build a separate AI to solve the challenge.In Part 1 - Optimizing Processes, we will build an AI that will optimize the flows in an E-Commerce warehouse!In Part 2 - Minimizing Costs, we will build a more advanced AI that will minimize the costs in energy consumption of a data center by more than 50%! Just as Google did last year thanks to DeepMind!In Part 3 - Maximizing Revenues, we will build a different AI that will maximize revenue of an Online Retail Business, making it earn more than 1 Billion dollars in revenue!But that's not all, this time, and for the first time, we've prepared a huge innovation for you. With this course, you will get an incredible extra product, highly valuable for your career:"a 100-pages book covering everything about Artificial Intelligence for Business!".The Book:This book includes:100 pages of crystal clear explanations, written in beautiful and clean latexAll the AI intuition and theory, including the math explained in detailThe three Case Studies of the course, and their solutionsThree different AI models, including Q-Learning, Deep Q-Learning, and Thompson SamplingCode TemplatesHomework and their solutions for you to practicePlus, lots of extra techniques and tips like saving and loading models, early stopping, and much much more.Conclusion:If you want to land a top-paying job or create your very own successful business in AI, then this is the course you need.Take your AI career to new heights today with Artificial Intelligence for Business -- the ultimate AI course to propel your career further.
Overview
Section 1: Introduction
Lecture 1 Welcome Challenge!
Lecture 2 Introduction
Lecture 3 Learning Paths
Lecture 4 The Book
Section 2: -------------------- PART 1 - OPTIMIZING BUSINESS PROCESSES --------------------
Lecture 5 Welcome to Part 1 - Optimizing Business Process
Section 3: Case Study
Lecture 6 Optimizing Business Processes - Step 1
Lecture 7 Optimizing Business Processes - Step 2
Lecture 8 Optimizing Business Processes - Step 3
Lecture 9 Optimizing Business Processes - Step 4
Section 4: AI Solution
Lecture 10 Welcome to the Intuition Section
Lecture 11 Plan of Attack
Lecture 12 What is Reinforcement Learning?
Lecture 13 The Bellman Equation
Lecture 14 The Plan
Lecture 15 Markov Decision Process
Lecture 16 Policy vs Plan
Lecture 17 Living Penalty
Lecture 18 Q-Learning Intuition
Lecture 19 Temporal Difference
Lecture 20 Q-Learning Visualization
Section 5: Implementation
Lecture 21 Optimizing Business Processes - Step 5
Lecture 22 Optimizing Business Processes - Step 6
Lecture 23 Optimizing Business Processes - Step 7
Lecture 24 Optimizing Business Processes - Step 8
Lecture 25 Optimizing Business Processes - Step 9
Lecture 26 Optimizing Business Processes - Step 10
Lecture 27 Optimizing Business Processes - Step 11
Lecture 28 Optimizing Business Processes - Step 12
Lecture 29 Optimizing Business Processes - Step 13
Lecture 30 Optimizing Business Processes - Step 14
Lecture 31 Optimizing Business Processes - Step 15
Lecture 32 Optimizing Business Processes - Step 16
Lecture 33 Optimizing Business Processes - Step 17
Lecture 34 Optimizing Business Processes - Step 18
Lecture 35 Optimizing Business Processes - Step 19
Lecture 36 Optimizing Business Processes - Step 20
Section 6: Homework
Lecture 37 Homework Instruction
Lecture 38 Homework Solution
Section 7: -------------------- PART 2 - MINIMIZING COSTS --------------------
Lecture 39 Welcome to Part 2 - Minimizing Costs
Section 8: Case Study
Lecture 40 Minimizing Costs - Step 1
Lecture 41 Minimizing Costs - Step 2
Lecture 42 Minimizing Costs - Step 3
Section 9: AI Solution
Lecture 43 Welcome to the Intuition Section
Lecture 44 Plan of Attack
Lecture 45 Deep Q-Learning Intuition - Step 1
Lecture 46 Deep Q-Learning Intuition - Step 2
Lecture 47 Experience Replay
Lecture 48 Action Selection Policies
Section 10: Implementation
Lecture 49 Minimizing Costs - Step 4
Lecture 50 Minimizing Costs - Step 5
Lecture 51 Minimizing Costs - Step 6
Lecture 52 Minimizing Costs - Step 7
Lecture 53 Minimizing Costs - Step 8
Lecture 54 Minimizing Costs - Step 9
Lecture 55 Minimizing Costs - Step 10
Lecture 56 Minimizing Costs - Step 11
Lecture 57 Minimizing Costs - Step 12
Lecture 58 Minimizing Costs - Step 13
Lecture 59 Minimizing Costs - Step 14
Lecture 60 Minimizing Costs - Step 15
Lecture 61 Minimizing Costs - Step 16
Lecture 62 Minimizing Costs - Step 17
Lecture 63 Minimizing Costs - Step 18
Lecture 64 Minimizing Costs - Step 19
Lecture 65 Minimizing Costs - Step 20
Lecture 66 Minimizing Costs - Step 21
Lecture 67 Minimizing Costs - Step 22
Lecture 68 Minimizing Costs - Step 23
Lecture 69 Minimizing Costs - Step 24
Lecture 70 Minimizing Costs - Step 25
Lecture 71 Minimizing Costs - Step 26
Lecture 72 Minimizing Costs - Step 27
Lecture 73 Minimizing Costs - Step 28
Lecture 74 Minimizing Costs - Step 29
Lecture 75 Minimizing Costs - Step 30
Lecture 76 Minimizing Costs - Step 31
Lecture 77 Minimizing Costs - Step 32
Lecture 78 Installing Keras
Lecture 79 Minimizing Costs - Step 33
Lecture 80 Minimizing Costs - Step 34
Lecture 81 Minimizing Costs - Step 35
Lecture 82 Minimizing Costs - Step 36
Section 11: Homework
Lecture 83 Homework Instruction
Lecture 84 Homework Solution
Lecture 85 Extra: Dropout
Section 12: -------------------- PART 3 - MAXIMIZING REVENUES --------------------
Lecture 86 Welcome to Part 3 - Maximizing Revenues
Section 13: Case Study
Lecture 87 Maximizing Revenues - Step 1
Lecture 88 Maximizing Revenues - Step 2
Lecture 89 Maximizing Revenues - Step 3
Section 14: AI Solution
Lecture 90 Welcome to the Intuition Section
Lecture 91 The Multi-Armed Bandit Problem
Lecture 92 Thompson Sampling Intuition
Section 15: Implementation
Lecture 93 Maximizing Revenues - Step 4
Lecture 94 Maximizing Revenues - Step 5
Lecture 95 Maximizing Revenues - Step 6
Lecture 96 Maximizing Revenues - Step 7
Lecture 97 Maximizing Revenues - Step 8
Lecture 98 Maximizing Revenues - Step 9
Lecture 99 Maximizing Revenues - Step 10
Lecture 100 Maximizing Revenues - Step 11
Lecture 101 Maximizing Revenues - Step 12
Lecture 102 Maximizing Revenues - Step 13
Lecture 103 Maximizing Revenues - Step 14
Lecture 104 Maximizing Revenues - Step 15
Lecture 105 Maximizing Revenues - Step 16
Section 16: Homework
Lecture 106 Homework Instruction
Lecture 107 Homework Solution
Lecture 108 THANK YOU Video
Section 17: Annex: Artificial Neural Networks
Lecture 109 Plan of Attack
Lecture 110 The Neuron
Lecture 111 The Activation Function
Lecture 112 How do Neural Networks work?
Lecture 113 How do Neural Networks learn?
Lecture 114 Gradient Descent
Lecture 115 Stochastic Gradient Descent
Lecture 116 Back-Propagation
Section 18: Congratulations!! Don't forget your Prize :)
Lecture 117 Huge Congrats for completing the challenge!
Lecture 118 Bonus: How To UNLOCK Top Salaries (Live Training)
Business Driven people, who are eager to learn how to leverage AI to optimize their Business, maximize profitability and efficiency,AI practitioners, who want to know what projects they can offer to their Employees,Aspiring Data Scientists, looking for Business Cases to add to their Portfolio,Technology Enthusiasts interested in leveraging Machine Learning and Artificial Intelligence to solve Business Problems,Consultants, who want to transition companies into AI Driven Businesses

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