Certified Reinforcement Learning Expert

16,888.00

Learn building AI agents for optimal decision-making and optimization problems.

  • Get certified for your knowledge
  • Work on projects and get experience certificate

Description

Reinforcement learning is one of the important subfields of machine learning concerned with developing intelligent applications that can learn from the environment. There are many important applications of reinforcement learning in optimization problems and taking optimal decisions. This certification-oriented course presents complete coverage of reinforcement learning with its key concepts along with its practical implementation in python. This course also let the attendees build reinforcement learning-based solutions for real-world use cases.

 

Program Outcome

  • Get job ready with a complete understanding of reinforcement learning and its key concepts
  • Hands-on knowledge of building reinforcement learning-based solutions for real-world use cases
  • Sound understanding of implementing reinforcement learning algorithms in python

Prerequisite

  • Basic knowledge of machine learning
  • Intermediate-level knowledge of python programming
  • Understanding of mathematical concepts

Mastering Reinforcement Learning: Course Content

  • Introduction and Overview

    Detailed introduction to reinforcement learning, popular algorithms and its applications.

  • Markov Decision Process (MDP)
    1. Introduction to MDP
    2. Working of MDP
    3. MDP and Reinforcement Learning
  • State–Action–Reward–State–Action (SARSA)
    1. Introduction to SARSA
    2. Familiarity with SARSA algorithm
  • Upper Confidence Bound

    Complete familiarity with Upper Confidence Bound with its implementation.

  • Thompson Sampling

    Complete familiarity with Thompson Sampling with its implementation.

  • Q-Learning

    Complete familiarity with Q-Learning with its implementation.

  • Deep Q-Learning

    Complete familiarity with Deep Q-Learning with its implementation.

  • OpenAI Gym

    Complete familiarity with OpenAI Gym framework with its implementation.

  • Reinforcement Learning Use Cases
    1. Use Cases in Investment
    2. Use Cases in Healthcare
    3. Use Cases in Gaming
    4. Use Cases in Decision Making
    5. Use Cases in Optimization
  • Reinforcement Learning and Web 3.0

    Understanding of how Reinforcement Learning is applied to Web 3.0

  • Capstone Project

    A complete project that covers the skills earned during the course with guidance from industry mentors and support from learner success managers throughout.

FAQS

  • Who can attend this course?

    This course is suitable for beginners as well as professionals working in different domains.

  • What is the mode of delivery?

    This course has different modes of delivery. It can be taken in person from a center over the weeks, or it can be taken online as well based on your own convenience.

  • Will there be an instructor also in this course?

    Yes, an instructor will be there for in-person delivery and online (instructor-led) delivery.

  • What are the prerequisites to attend this course?

    Basic understanding of machine learning, python, and mathematics is required to attend this course.

  • How difficult is this course to learn?

    The course has beginner-level difficulty.

  • What job roles can i take if i attend this course?

    Data scientists, Reinforcement learning engineer, AI Scientists, etc. roles can be explored after taking this course.

  • Who can get the certificate?

    All attendees who complete all sections of the course along with the capstone project will get the certificate.

  • How the completeness of each section is measured in the course?

    There are MCQ-based short tests given after each section to assess the understanding of a learner in each section. Finally, the capstone project is evaluated manually by the instructors.

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