Deep Reinforcement Learning for Beginners

Introduction:

Empower your AI journey through our Reinforcement Learning course. Discover the intricacies of this machine learning method that enables machines and software agents to learn optimal behaviors in specific environments. Reinforcement Learning is gaining popularity as a pivotal tool for studying and enhancing machine and software agents’ actions, fostering autonomous systems that continually improve through experience. Learn, upskill, and deepen your knowledge in AI with our comprehensive training.

Course Objectives:

  • Q Learning
  • Sarsa
  • Deep Q-Network
  • Open AI Gym
  • Policy Gradient
  • Actor Critic

Duration

7 hours, 1 Day Course

Mode of Delivery

Classroom-based, Instructor-led Training

Course Outlines

  1. Introduction to RL
    1. What is Reinforcement Learning (RL)
    2. Basic Concepts of RL
    3. Applications of RL
    4. RL Approaches
    5. Key RL Algorithms
  2. Q Learning
    1. What is Q-Learning?
    2. Q-Value, Discount Factor and Learning Rate
    3. Q Table Update
    4. Policy
    5. Q-Learning Algorithm
    6. Q-Learning Demo
  3. Sarsa
    1. What is Sarsa?
    2. Q Value Update
    3. Sarsa Algorithm
    4. Sarsa Demo
  4. Open AI Gym
    1. OpenAI Gym
    2. Install Gym
    3. Render Gym Env
    4. Action on Gym Env
    5. Q-Learning on Gym Env
  5. Deep Q-Network
    1. What is Deep Q Network (DQN)?
    2. DQN Loss Function
    3. Experience Replay
    4. DQN Algorithm
    5. DQN Demo
    6. Atari DQN
  6. Policy Gradient
    1. What is Policy Gradient (PG)?
    2. PG Algorithm
    3. PG Demo
  7. Actor-Critic
    1. What is Actor-Critic?
    2. Actor Critic Algorithm
    3. Actor Critic Demo
    4. Alpha Go