Deep Reinforcement Learning using python 2025

Course Overview

• Course Title: Deep Reinforcement Learning using python 2025
• Instructor: Riad Almadani
• Target Audience:
  • Intermediate to advanced learners in machine learning
  • Individuals interested in deep reinforcement learning and AI
  • Developers looking to build smart robots
• Prerequisites:
  • Numpy, Matplotlib, Pandas
  • Gradient descent
  • Object-oriented programming
  • General understanding of deep learning

Curriculum Highlights

• Key Topics Covered:
  • An Introduction to Deep Reinforcement Learning
  • Setting up the environment
  • Grid World Game & Deep Q-Learning
  • Mountain Car game & Deep Q-Learning
  • Flappy bird game & Deep Q-learning
  • Ms Pacman game & Deep Q-Learning
  • Stock trading & Deep Q-Learning
• Key Skills Learned:
  • Understanding deep reinforcement learning and its applications
  • Building neural networks
  • Implementing reinforcement learning projects
  • Improving robot capabilities
  • Building variants of Q network

Course Format

• Duration: 9 hours on-demand video
• Format: Self-paced online course
• Resources:
  • 2 downloadable resources
  • Access on mobile and TV
  • Closed captions
  • Audio description in existing audio
  • Certificate of completion