Check our FREE resources
Learn More

AI-4: Generative Models & Reinforcement Learning

This course will provide you with the fundamental understanding of the concepts behind Generative Models and Reinforcement Learning and apply them to real world problems.


Split into 2 parts, the course starts with generative models which cover autoencoders, variational autoencoders and Generative Adversarial Networks. The second half of this course will introduce you to the field of Reinforcement Learning. At the end of the course, you will be able to build efficient generative models, and work with reinforcement learning problems.


This course will prepare you for elite, much sought after AI positions. It will also equip you to conduct original research in your area of interest.

Program image
Applications opening soon
Registration Closed

Starts

June 14, 2021
To be decided
Self-paced

Duration

6 weeks

Format

Live Online
Online

Time Investment

10 to 15 hours per week
Online

Fee

₹40,000.00

(Interest free EMI available)

Registration closes

June 10, 2021
To be decided

Course Outcome

Program Overview

Program Overview

After successfully completing the program, you will be:


  • Able to write natural language products such as question-answers, and build new ones
  • Able to write intelligent robot routines and control systems (for eg., healthcare) that will use autonomous agents
  • Awarded an advanced certification in AI 
  • Eligible to be a part of the Capstone internship program
  • Prepared to pursue advanced (graduate, doctorate) level studies in AI
  • Qualified to seek upper-intermediate and senior level AI positions in the industry

After successfully completing the program, you will be:

  • Able to write natural language products such as question-answers, and build new ones.
  • Able to write intelligent robot routines and control systems (for eg., healthcare) that will use autonomous agents.
  • Awarded an advanced certification in AI. 
  • Eligible to be a part of the Capstone internship program.
  • Prepared to pursue advanced (graduate, doctorate) level studies in AI.
  • Qualified to seek upper-intermediate and senior level AI positions in the industry.

Who should apply

Prerequisites

Learners and practitioners who have an understanding of intermediate AI concepts including Language Modeling and Transfer Models and are looking to master more advanced concepts. You should have strong foundations in statistics, computer science & mathematics.

See if you are ready

Knowledge of beginning and intermediate AI as exemplified by the topics in AI: Basics

Able to build complex language models and gauge their performance, as covered in AI 3

Prior knowledge of high level machine learning libraries such as keras


Course Structure

Live online classes
1. Live Online Classes

Bi-weekly lessons with labs and quizzes

Mentorship
2. Mentor-Supported

Ten or more hours/week to interact with an experienced & accomplished mentor

Module end Project
3. End-of-Module Project

Complex problems that challenge you to apply what you learned

Capstone
4. Capstone

10–12 week long Capstone Project with one of our partner companies or faculty

Program Faculty

No items found.

Topics Covered

AI 4

GANs
Markov Decision Processes
Deep Q Networks
Policy Gradient Methods
Actor Critic models
Model based methods

Project Week

Our Alumni

More reviews

Our Alumni are at

Financial Assistance

Interest free EMI

Our programs are priced for access, and are affordable for most around the world who seek the best training in sought after areas like AI and Data Science. For those who might still need financing, we have EMI payments available.

Scholarship for the best

A small number of Univ.AI Scholarships are available for the best candidates. Learn More

Tell a friend about our program

And we'll give you both Amazon vouchers worth ₹ 5,000

Learn more

Frequently Asked Questions

No items found.
More answers

Request more information

By submitting your email, you agree to our privacy policy
Thank you! Our team will contact you shortly.
Oops! Something went wrong while submitting the form.