Artificial Intelligence for Simple Games

Description

Ever wish you could harness the power of Deep Learning and Machine Learning to create intelligent bots for gaming?

If you’re searching for an exciting and creative way to explore Artificial Intelligence, then ‘Artificial Intelligence for Simple Games’ is your gateway to building lasting skills.

In this course, you’ll learn and test your AI knowledge of essential DL and ML algorithms through the engaging and flexible environment of simple games like Snake, the Travelling Salesman problem, mazes, and more.

Whether you’re brand new to AI or an experienced Machine Learning expert, this course delivers a strong foundation in both basic and advanced concepts you’ll need to build AI within gaming—and extend your skills far beyond.

Key algorithms and concepts covered in this course include: Genetic Algorithms, Q-Learning, Deep Q-Learning with both Artificial Neural Networks and Convolutional Neural Networks.

Dive into SuperDataScience’s renowned, interactive learning approach that gradually builds your knowledge and intuition through practical and challenging case studies.

Thanks to flexible code examples, you’ll be able to experiment with different game scenarios and easily translate your learning to business problems outside the gaming industry.

‘AI for Simple Games’ Curriculum

• Section #1 — Explore Genetic Algorithms by applying the classic Travelling Salesman Problem to a space-themed game. Your mission: build a spaceship that travels between planets in the shortest time possible!

• Section #2 — Master the fundamentals of the model-free reinforcement learning algorithm, Q-Learning. Develop intuition and visualization skills as you build a custom maze and design an AI capable of finding its way out.

• Section #3 — Delve into Deep Q-Learning. Discover the fascinating world of Neural Networks using the OpenAI Gym development environment, and learn how to build AIs for numerous simple games!

• Section #4 — Wrap up the course by creating your own version of the classic game Snake! You’ll apply Convolutional Neural Networks to build an AI that replicates the same intelligent behavior we observe when playing Snake.

By the end of this course, you’ll be equipped with practical skills and deep understanding, ready to tackle AI projects both in gaming and in broader real-world applications.