Learn To Create Artificially Intelligent Games Using Python3

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Setup Anaconda and Install Dependencies for Project

Lecture 1: Install Anaconda

Lecture 2: Create Virtual Environment

Lecture 3: Install Dependencies/Libraries for the Course

Lecture 4: Download Visual Studio Code

Chapter 3: Python Essentials

Lecture 1: What is Python?

Lecture 2: Introduction to the data types

Lecture 3: Basic Arithmetic in Python

Lecture 4: Operations on Numbers

Lecture 5: Introduction to Strings in Python

Lecture 6: Access elements of String

Lecture 7: Formatting strings

Lecture 8: Introduction to the variables

Lecture 9: Create Variables in Python

Lecture 10: Introduction to Booleans in Python

Lecture 11: Learn to create conditions

Lecture 12: "is" operator in Python

Lecture 13: Logical statements

Lecture 14: Introduction to conditional statements

Lecture 15: if else statements

Lecture 16: Introduction to Data Structures

Lecture 17: Checking type of Data Structures

Lecture 18: How to access the items from the list?

Lecture 19: Introduction to the loops in Python

Lecture 20: Infinite while loop (Game Loop)

Lecture 21: Finite Game Loop

Lecture 22: For loop

Lecture 23: Important: List Comprehension for Game Development

Lecture 24: What is Function and Why we need it?

Lecture 25: Learn to create Functions?

Lecture 26: Learn about return statements

Lecture 27: Introduction to the section

Lecture 28: What is Object Oriented Programming?

Lecture 29: Class and Objects

Lecture 30: Class and Objects Continued

Lecture 31: Constructor in Python

Lecture 32: What is Inheritance?

Lecture 33: Multiple Inheritance

Chapter 4: Pygame Refresher

Lecture 1: Introduction to the pygame

Lecture 2: Pygame coordinate System

Lecture 3: Introduction to Pygame shape

Lecture 4: Draw shapes using Pygame

Lecture 5: Color Picker

Lecture 6: Fundamentals of Pygame — skeleton code

Lecture 7: Render a rectangle in the Screen

Lecture 8: Movement of the shapes

Lecture 9: Smoothen the movement using FPS

Lecture 10: Make movement within Boundary

Chapter 5: Introduction to MinMax Algorithm

Lecture 1: Introduction to Board Games

Lecture 2: Tree representation of Game

Lecture 3: Lookahead Problem

Lecture 4: Solution of Lookahead problem

Lecture 5: Heuristic Evaluation of Board

Lecture 6: Example of Heuristic

Lecture 7: Introduction to MinMax algorithm

Lecture 8: Example of MinMax

Lecture 9: MinMax Example for TicTacToe

Lecture 10: MinMax Algorithm

Chapter 6: Creating TicTacToe using MinMax algorithm

Lecture 1: introduction to Game

Lecture 2: Introduction to Project Files

Lecture 3: Creating Indecisive Player (Random)

Lecture 4: Implementing MinMax

Lecture 5: Calculating Value/Heuristic for Min Max player

Lecture 6: Implementing MinMax algorithm

Lecture 7: Setting up Autoplayer (Artificial Intelligent Player)

Lecture 8: Playing against AI player and Tuning algorithm

Chapter 7: Introduction to Artificial Intelligence

Lecture 1: Motivation for Artificial Intelligence

Lecture 2: Reinforcement Learning

Lecture 3: Environment

Lecture 4: Rewards

Lecture 5: Path

Lecture 6: Typical RL scenario

Lecture 7: Policy

Lecture 8: Rewards

Lecture 9: Value of the State

Lecture 10: Model

Chapter 8: Key Terms of Artificial Intelligence (Important)

Lecture 1: Markov Property and Markov Chain

Lecture 2: Markov Reward Process

Lecture 3: Markov Decision Process

Chapter 9: Bellman Equation and Dynamic Programming

Lecture 1: Introduction

Lecture 2: Tribute to Bellman

Lecture 3: Value Function

Lecture 4: Bellman Equation

Lecture 5: Example

Lecture 6: Plan

Lecture 7: Non Deterministic Environment

Lecture 8: Markov Decision Process + Bellman

Lecture 9: Introduction to Q-Learning

Lecture 10: Equation of Q-Learning

Lecture 11: Q value for Non-Deterministic Environment

Lecture 12: Temporal Difference