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Advanced Reinforcement Learning 
offered by MIT University

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Advanced Reinforcement Learning
 at 
MIT University 
Overview

Explore the cutting-edge of RL research, and enhance the ability to identify the correct approach for applying advanced frameworks to pressing industry challenges

Duration

2 days

Start from

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Total fee

2.07 Lakh

Mode of learning

Online

Schedule type

Self paced

Official Website

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Course Level

UG Certificate

Advanced Reinforcement Learning
 at 
MIT University 
Highlights

  • Earn a certificate after completion of the course
  • Learn from industry experts
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Advanced Reinforcement Learning
 at 
MIT University 
Course details

Who should do this course?
  • For Research scientists
  • For Data scientists
  • For Data analysts and business analysts
  • For Machine learning engineers and software engineers
  • For Product managers and program managers
  • For CTOs and other technology leaders
What are the course deliverables?
  • Determine the reinforcement learning framework (e.g. goal-directed, hierarchical, offline reinforcement learning, bandits) that is best-suited to solve a specific problem
  • Select the most promising algorithms for an already-formulated reinforcement learning problem
  • Recognize the limitations of reinforcement learning in order to judge whether a situation is suited for these strategies
More about this course
  • This course is tailored for individuals seeking an in-depth exploration of cutting-edge concepts and applications in the field of reinforcement learning (RL)
  • In this course participants will gain insights into how advanced RL methods are reshaping industries and solving complex decision-making problems

Advanced Reinforcement Learning
 at 
MIT University 
Curriculum

Exploration in Complex Environments

Multi-Agent Reinforcement Learning (MARL)

Deep Reinforcement Learning (DRL)

Hierarchical Reinforcement Learning

Meta-Reinforcement Learning

Off-Policy Reinforcement Learning

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Advanced Reinforcement Learning
 at 
MIT University 
Faculty details

Pulkit Agrawal
Pulkit Agrawal is assistant professor of electrical engineering and computer science at MIT and leads the Improbable AI Lab, part of the Computer Science and Artificial Intelligence Lab at MIT and affiliated with the Laboratory for Information and Decision Systems.
Cathy Wu
Cathy Wu is the Gilbert W. Winslow Career Development Assistant Professor of civil and environmental engineering at MIT and has worked across many fields and organizations, including Microsoft Research, OpenAI, the Google X Self-Driving Car Team, AT&T, Caltrans, Facebook, and Dropbox.

Advanced Reinforcement Learning
 at 
MIT University 
Entry Requirements

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Advanced Reinforcement Learning
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Cambridge ( Massachusetts)

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