Future Artificial Intelligence Reinforcement Learning (TM)

Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: A2C, REINFORCE, DQN, etc.

Created by: Escape Velocity Labs
Hands-on, comprehensive AI courses

What Will I Learn?

• Understand the Reinforcement Learning paradigm and the tasks that it's best suited to solve.
• Understand the process of solving a cognitive task using Reinforcement Learning
• Understand the different approaches to solving a task using Reinforcement Learning and choose the most fitting
• Implement Reinforcement Learning algorithms completely from scratch
• Fundamentally understand the learning process for each algorithm
• Debug and extend the algorithms presented
• Understand and implement new algorithms from research papers

Requirements

• Be comfortable programming in Python
• Know basic linear algebra and calculus (matrices, vectors, determinants, derivatives, etc.)
• Know basic statistics and probability theory (mean, variance, normal distribution, etc.)

Target audience

• Developers who want to get a job in Machine Learning
• Data scientists/analysts and ML practitioners seeking to expand their breadth of knowledge.
• Researchers/scholars seeking to enhance their practical coding skills.