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Deep Learning and Machine Learning on Raspberry Pi with Tensorflow
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Basic Reinforcement Learning with Python

Unlock the potential of Reinforcement Learning (RL) with our meticulously crafted course at Tertiary Courses. Gain a foundational grasp of the intricate concepts of Markov Decision Process (MDP) and Reinforcement Learning (RL), ensuring a robust grounding in this cutting-edge AI technology. Our course also offers hands-on experience, allowing participants to learn and apply RL using the renowned OpenAI Gym and Stable Baselines.

Venture deeper into the realms of Q-Learning, DQN, and Policy Gradient, with our interactive coding sessions, ensuring not just theoretical knowledge but practical expertise. By the end of the course, participants will be adept in crafting sophisticated RL solutions using Python, setting them on the path to AI excellence. Embrace the future of AI with our comprehensive Reinforcement Learning training.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant Applications

No funding is available for this course

For WSQ funding, please checkout the details at WSQ - Reinforcement Learning Course

Course Code: C625

Course Booking

The course fee listed below is before subsidy/grant, if applicable. We will apply for the grant and send you the invoice with nett fee.

$300.00 (GST-exclusive)
$327.00 (GST-inclusive)

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Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1 Introduction to Reinforcement Learning

  • Fundamental Concepts of Reinforcement Learning (RL)
  • Types of RL Algorithms
  • Applications of RL
  • Markov Decision Process

Topic 2 OpenAI Gym and Stable Baselines

  • Introduction to OpenAI Gym
  • Install OpenAI Gym and Stable Baselines
  • Create Agent and Policy on Gym

Topic 3 Value Based Q-Learning

  • Overview of Value Based Learning
  • Value Functions and Bellman's Equations
  • Exploration Strategies
  • Q-Learning Algorithm
  • SARSA Algorithm
  • Deep Q Network (DQN) Algorithm

Topic 4 Policy Based Learning

  • Overview of Policy Based Learning
  • Policy Network
  • Policy Gradient Algorithm

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