Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:

  • How to start building AI with no previous coding experience using Python
  • How to merge AI with OpenAI Gym to learn as effectively as possible
  • How to optimize your AI to reach its maximum potential in the real world

Here is what you will get with this course:


1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

2. Code templates – Plus, you’ll get downloadable Python code templates for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.

3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.

4. Real-world solutions – You’ll achieve your goal in not only 1 game but in 3. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.

Who this course is for:
  • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning

Course Curriculum

  • 1

    Welcome to the course!

    • Why AI?

    • Course Structure

    • Installing Anaconda
  • 2

    ---------- Part 0 - Fundamentals Of Reinforcement Learning ----------

    • Welcome to Part 0 - Fundamentals of Reinforcement Learning
  • 3

    Q-Learning Intuition

    • Plan of Attack

    • What is reinforcement learning?

    • The Bellman Equation

    • The "Plan"

    • Markov Decision Process

    • Policy vs Plan

    • Adding a "Living Penalty"

    • Q-Learning Intuition

    • Temporal Difference
  • 4

    Q-Learning Visualization

    • Q-Learning Visualization
  • 5

    ---------- Part 1 - Deep Q-Learning ----------

    • Welcome to Part 1 - Deep Q-Learning
  • 6

    Deep Q-Learning Intuition

    • Plan of Attack

    • Deep Q-Learning Intuition - Learning

    • Deep Q-Learning Intuition - Acting

    • Experience Replay

    • Action Selection Policies
  • 7

    Deep Q-Learning Implementation

    • Plan of Attack

    • Where to get the Materials

    • Getting Started

    • Self Driving Car - Step 1

    • Self Driving Car - Step 2

    • Self Driving Car - Step 3

    • Self Driving Car - Step 4

    • Self Driving Car - Step 5

    • Self Driving Car - Step 6

    • Self Driving Car - Step 7

    • Self Driving Car - Step 8

    • Self Driving Car - Step 9

    • Self Driving Car - Step 10

    • Self Driving Car - Step 11

    • Self Driving Car - Step 12

    • Self Driving Car - Step 13

    • Self Driving Car - Step 14

    • Self Driving Car - Step 15

    • Self Driving Car - Step 16
  • 8

    ---------- Part 2 - Deep Convolutional Q-Learning ----------

    • Welcome to Part 2 - Deep Convolutional Q-Learning
  • 9

    Deep Convolutional Q-Learning Intuition

    • Plan of Attack

    • Deep Convolutional Q-Learning Intuition

    • Eligibility Trace
  • 10

    Deep Convolutional Q-Learning Implementation

    • Plan of Attack

    • Doom - Step 1

    • Where to get the Materials

    • Doom - Step 2

    • Doom - Step 3

    • Doom - Step 4

    • Doom - Step 5

    • Doom - Step 6

    • Doom - Step 7

    • Doom - Step 8

    • Doom - Step 9

    • Doom - Step 10

    • Doom - Step 11

    • Doom - Step 12

    • Doom - Step 13

    • Doom - Step 14

    • Doom - Step 15

    • Doom - Step 16

    • Doom - Step 17
  • 11

    Deep Convolutional Q-Learning Visualization

    • Watching our AI play Doom
  • 12

    Deep Q-Learning Visualization

    • Self Driving Car - Level 1

    • Self Driving Car - Level 2

    • Self Driving Car - Level 3

    • Self Driving Car - Level 4

    • Challenge Solutions

  • 13

    ---------- Part 3 - A3C ----------

    • Welcome to Part 3 - A3C
  • 14

    A3C Intuition

    • Plan of Attack

    • The three A's in A3C

    • Actor-Critic

    • Asynchronous

    • Advantage

    • LSTM Layer
  • 15

    A3C Implementation

    • Plan of Attack

    • Where to get the Materials

    • Breakout - Step 1

    • Breakout - Step 2

    • Breakout - Step 3

    • Breakout - Step 4

    • Breakout - Step 5

    • Breakout - Step 6

    • Breakout - Step 7

    • Breakout - Step 8

    • Breakout - Step 9

    • Breakout - Step 10

    • Breakout - Step 11

    • Breakout - Step 12

    • Breakout - Step 13

    • Breakout - Step 14
  • 16

    A3C Visualization

    • Watching our AI play Breakout
  • 17

    Annex 1: Artificial Neural Networks

    • What is Deep Learning?

    • Plan of Attack

    • The Neuron

    • The Activation Function

    • How do Neural Networks work?

    • How do Neural Networks learn?

    • Gradient Descent

    • Stochastic Gradient Descent

    • Backpropagation
  • 18

    Annex 2: Convolutional Neural Networks

    • Plan of Attack

    • What are convolutional neural networks?

    • Step 1 - Convolution Operation

    • Step 1(b) - ReLU Layer

    • Step 2 - Pooling

    • Step 3 - Flattening

    • Step 4 - Full Connection

    • Summary

    • Softmax & Cross-Entropy

About the instructor

IT Manager

Eric Chu

A proven and experienced IT Manager, customer-focused and equipped with a technical background. I have over 8 years’ experience in IT Service Delivery Management and leading small to medium crossfunctional teams, and over 15 years of experience in IT Training and Sales.Through my passion for technology, science, and innovation, I have fostered extensive practical knowledge of emerging technologies, complex networks, and data centre eco-systems.I have had the opportunity to work across the Asia Pacific region as an experienced Business Development Manager and IT Project Manager delivering end to end solutions.

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