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PG Program – Artificial Intelligence & Machine Learning

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Application Deadline - 19th April 2018

Why PGP - Artificial Intelligence & Machine Learning


covers the most popular and widely used AI & ML technologies and applications including Deep Learning, Computer Vision, NLP, Intelligent Virtual Agents, Neural Network, Tensor Flow, etc.

2 Million+ Learning Hours

We have delivered more than 2 million learning hours to our students and alumni.

India's Top Ranked Institute

Great Lakes has been the preferred choice of technology professional for over 13 years now.


Dual Certification from Great Lakes & Stuart School of Business, IIT Chicago.

7 Top Reasons to Join PGP – AI & ML

The Post Graduate Program in Artificial Intelligence and Machine Learning is designed to develop competence in AI and ML for future-oriented working professionals. PGP-AIML is a 12-month program offered in blended format with weekend classroom sessions and online learning.

Employers, leaders and managers all agree on one thing – it is not what you know, but what you can do that matters. And that is our learning philosophy.


PGP-AIML is a rigorous and hands-on program with sessions using AI & ML lab and 8 mini projects. You will work on a series of projects and build an e-portfolio of tangible projects and achievements that you can use to demonstrate what you can do.

It features case studies and learning from some of the top global companies like Uber, Netflix, Google, Amazon etc. With case studies, labs and projects, you will develop a practitioner’s understanding of applicability, trade-offs and suitability of various techniques to a variety of problems you’re likely to face.


The program builds a solid foundation by covering the most popular and widely used Artificial Intelligence & Machine Learning technologies and applications including Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Intelligent Virtual Agents, Neural Network, Tensor Flow and even reinforcement learning – laying the building blocks for truly expanded capabilities.


Not just an introduction to neural networks and deep learning, you will spend nearly half the program getting your hands dirty with neural networks, deep neural networks and their variations in CNN and RNN.


Through a blended mode of delivery, with minimal disruption to your job, you get the best of both worlds – rigorous exploration of the conceptual elements in class amidst your peers and faculty, and continuous practice online to reinforce the learning.


You are provided career support through resume workshops and interview preparation sessions. Relevant career opportunities with leading companies are also shared with candidates.


Great Lakes has consistently been ranked in Top 10 Institutes in the country by Analytics India Magazine, Outlook, Business India and others, and has been the preferred choice for Technology Professionals for over 13 years.


By virtue of being part of an internationally recognized program, you will receive dual certificate from Stuart School of Business, Illinois Institute of technology, Chicago (USA) and Great Lakes Institute of Management.

Program Structure

The Post Graduate Program in Artificial Intelligence and Machine Learning is designed to develop competence in AI and ML for future-oriented working professionals. PGP-AIML is a 12-month blended program with weekend classroom sessions and online learning. Classes will be held one weekend a month at the Great Learning centre and supplemented by online learning content. The program constitutes of nearly 400 learning hours with 250 classroom learning hours. Classroom sessions are held one weekend a month, alternating as 3 days (Friday, Saturday, and Sunday) and 2 days (Saturday and Sunday) each month.

Delivery Mode of the program

  • Weekend Classroom + Online Learning
  • Learn by doing (Hands-on Sessions using AI and ML lab)
  • Learning from both academic faculty and industry practitioner experts
  • Peer Learning

Learning Outcomes

  • Develop expertise in popular AI & ML technologies and problem-solving methodologies
  • Develop ability to independently solve business problems using AI & ML
  • Learn to use popular AI & ML technologies like Python, Tensorflow and Keras to develop applications
  • Develop a verified portfolio with 8 projects that will showcase the new skills acquired

Program Curriculum

Foundations of AI

Topics Covered

  • Python for AI (Significant Functions, Packages and Routines)
  • Statistics & Probability (Descriptive & Inferential Stats, Probability & Conditional Prob)
  • Visualization principles and techniques

Machine Learning: Supervised Learning

Topics Covered

  • Regression (Linear, Multiple, Logistic)
  • Classification (k-NN, naïve Bayes) techniques
  • Decision Trees

Machine Learning: Unsupervised Learning

Topics Covered

  • Clustering (k-means, hierarchical, high-dimensional)
  • Expectation Maximization

Machine Learning: Ensemble Techniques

Topics Covered

  • Boosting and Bagging
  • Random Forests

Machine Learning: Reinforcement Learning

Topics Covered

  • Value-based methods (e.g. Q-learning)
  • Policy-based methods

Deep Learning

Topics Covered

  • Neural Network Basics
  • Deep Neural Networks
  • Recurrent Neural Networks (RNN)
  • Deep Learning applied to Images using CNN
  • Tensor Flow for Neural Networks & Deep Learning

Computer Vision

Topics Covered

  • Convolutional Neural Networks
  • Keras library for deep learning in Python
  • Pre-processing Image Data
  • Object & face recognition using techniques above

Natural Language Processing

Topics Covered

  • Statistical NLP and text similarity
  • Syntax and Parsing techniques
  • Text Summarization Techniques
  • Semantics and Generation

Intelligent Agents

Topics Covered

  • Uninformed and heuristic-based search techniques
  • Adversarial search and its uses
  • Planning and constraint satisfaction techniques

Projects & Tools

During the program duration, candidates will work on projects that will involve hands-on exposure to the following tools:

  • Python
  • Data Libraries such as Pandas, Numpy, Scipy
  • Python Machine Learning library such as scikit-learn
  • Python visualization library such as Matplotlib
  • Natural Language Processing library such as NLTK
  • Tensor Flow
  • Keras

In addition to this, there will be 8 mini projects spread across topics such as:

  • Supervised Learning
  • Unsupervised Learning
  • Ensemble Techniques
  • Reinforcement Learning
  • Deep Learning
  • NLP
  • Computer Vision using data from companies such as Uber, Netflix, AplhaGo (Google), Amazon.

Candidates will also get access to an AI lab where they will use techniques they learn (in areas such as machine learning and deep learning) and solve problems in Computer Vision and Natural Language Processing.



Here’s a sampling of some of the case studies, labs and projects you will be working on as part of this program.

A campaign to sell personal loans

Identify potential customers for a personal loan product for a bank, allowing the bank to design targeted marketing campaigns to increase conversion.

Predictive analytics of taxi demand

Using data on New York City’s taxi supply and commuter demand, additional data from Uber, and extraneous factors; forecast demand and make predictions on wait times for a taxi.

Customer sentiment from Amazon reviews

Build machine learning models that can determine and predict the sentiment from text reviews on Amazon’s website.

Visualizing vintage art sales

Use a variety of visualization techniques to understand the features of paintings and purchase patterns across the American art market.

Handwritten digit recognition

Given a series of handwritten digits, interpret these images and classify them appropriately to display actual numbers using neural networks.

Logistics/Delivery planning

Using planning frameworks and appropriate search techniques, learn to solve a logistics planning problem that is traditionally one of the hardest (and most impactful) problems for a host of companies.

Network intrusion detection

Build a network intrusion detection system and improve the accuracy of your prediction using a series of ensemble techniques.

This is just a small, indicative sample of the kinds of problems you will learn to solve as part of this program. Faculty are constantly working to expose you to a broad array of scenarios and you can expect other such problems as part of your coursework.


Learn from the Best

Learn from the leading academicians in the field of AI and ML and several experienced industry practitioners from leading organizations. An indicative list of AIML experts engaged with us include:

Dr. Narayana Darapaneni

Professor, Big Data & Machine Learning

Dr. R.L. Shankar

Professor, Finance & Analytics

Dr. Mudit Kulshreshtha

Co-Director - Analytics Center of Excellence

Mukesh Rao

Consultant, Big Data & Machine Learning

Gurumoorthy P

Consultant, Big Data & Machine Learning

Prof. Raghavshyam

Adjunct Faculty, Data Visualization

Sajan Kedia

Data Scientist, Myntra

Jayatu Sen Chaudhury

Vice President - American Express


Admission Details for the PG Program - Artificial Intelligence & Machine Learning

The admissions are conducted on rolling bases and the admission process is closed once the requisite number of candidates have been enrolled in the program.


Applicants should have a minimum of 5 years of experience in a technology role, including at least 2 years of programming experience preferably in Python. For candidates who do not know Python, we offer a free pre-program tutorial.

Familiarity with statistics, algebra, and probability and exposure to data analysis is preferred.

Selection Process

Interested candidates need to apply by filling a simple online application form. Following which you will need to go through a screening process which happens over a call with the Admission Director's office. Post screening, your profile along with the review from the screening panel will be shared with the Program Director for final selection.

*Admissions will be closed once the requisite number of candidates have been admitted into the program.


Admission Details for the PG Program - AIML

Following are the payment details for the program:


Rs.3,25,000+ GST

Includes tuition fees, lab access, learning material and cafeteria access on the days of classes.



Candidates can pay the program fee through Cheque, DD, Net Banking, Credit Cards or Debit Cards.*

*Great Learning does not accept cash payments and issues receipts for all fee payments made towards all our programs.

Financial aid

Our tie-ups with several lending partners like HDFC Credila, MoneyTap, Credifiable, Axis Bank, and Avanse Education, for students who need financial help, ensure that money is not a constraint in the path of learning.


Mark the Dates

 Here are the Application Deadlines for the program

Application Deadline: 19 April 2018

We follow a rolling admission process and admissions are closed once the requisite number of participants enroll for the upcoming batch. So we encourage you to apply early and secure your seat. Apply Now

Batch commencement dates


11 May, 2018

Need More Information? Download PGP - Artificial Intelligence & Machine Learning course e Brochure for complete information.