What will you learn in this program?

Prof. Arjun Jain

Adjunct Faculty, IIT Bombay
Ph.D from Max Planck Institute
Part of Theano & Torch development teams


80+ hours of learning

Hands on projects

Live support sessions

Great Lakes Certificate

GPU accelerated Cloud Lab

Industry sessions

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Learn from IIT Bombay & Great Lakes Faculty

Dr. Arjun Jain

Adjunct Faculty for Deep Learning and Computer Vision, IIT Bombay

Dr. Jain is the co-founder of Perceptive Code, a Silicon Valley AI startup that builds intelligence into automobiles using Deep Learning. He is part of the Theano development team and a contributor to Torch - both of which are widely used libraries for Deep Learning.

Dr. Jain received his PhD from the Max Planck Institute in Germany and his post-doc from NYU where he worked with Yann LeCun.

Dr. Amit Sethi

Faculty for Image Processing and Machine Learning, IIT Bombay

Prof. Sethi is currently a faculty member at IIT Bombay where his research is focused on applying deep learning methodologies to digital pathology for analysis of cancer tissues. He was previously a faculty member at IIT Guwahati and spent many years at ZS Associates, a leading management consulting firm, at their offices in Chicago.

Prof. Sethi holds MS and PhD degrees from University of Illinois at Urbana-Champaign and BTech from IIT Delhi.

Prof. Mukesh Rao

Faculty, Machine Learning, Great Learning

Prof. Mukesh Rao has almost 3 decades of experience in the Analytics and Machine Learning industry. He has designed and implemented Machine Learning algorithms for abuse detection, social media analysis and report generation using MapReduce. Prior to this, Prof. Rao was with Wipro for over 12 years where he was the Head of PM Academy.

Program Benefits

World Class Faculty

Our faculty has been integral to the development and widespread adoption of Deep Learning. They have taught at the best institutions in the world and have worked with the likes of Yann LeCun, a founding father of Convolutional Networks. Our faculty has also spent years honing their craft in the financial, automotive and healthcare industries.

Guided hands-on Projects

Build confidence in your ability to build functional models through a series of industry-relevant deep learning projects. These hands-on projects, with guidance from the program’s learning support team, will give you an opportunity to learn by doing. Through this program, you will build an e-portfolio to showcase your expertise to the world.

Structured Learning

The program takes a step-by-step approach to learning as we walk you through all the elements of neural networks, deep learning and their application to computer vision and natural language processing. Every week, the learning content will be augmented by learning support sessions that will answer your questions and guide you through projects.

Labs with GPU access

Work on our accelerated computing platform with GPUs and all other software tools that you will need to build and test deep learning models on complex data sets. You can access this lab from anywhere and won’t need to struggle with lack of computing power and incompatibility issues.

India’s top ranked institute for analytics

Great Lakes has delivered India’s #1 program in analytics for the last 3 years (according to Analytics India magazine) and has been ranked among the best institutes in the country by Outlook, Business India and others for over 13 years.

How it works

DLCP is a 3-month structured online program with hands-on projects and learning support, all designed to help you become proficient in deep learning. You will be able to show current and future employers what you can do through an online e-portfolio of projects and tools that you’ve worked on as part of this program.

Program Structure

Online content from world-class faculty + Learning support sessions + Hands-on projects

  • Online content

    Best-in-class content from expert faculty and industry sessions

  • Hands-on projects

    Solve real-world problems using widely used deep learning techniques

  • Weekly learning support sessions

    Live support sessions to guide your learning journey



Foundations of Deep Learning
  • Loss function
  • Cross entropy
  • K – nearest neighbour algorithm
  • Minimizing the error – regression problem
  • Essentials of Neural Networks
  • Gradient Descent
  • Feed forward & Back propagation algorithm
  • Learning rate
  • Multi-layer Deep Neural Networks
  • Hyper parameter selection
  • Weight initialization
  • Deep Learning architectures
  • Convolutional Neural Networks (CNN)
  • Image processing using CNN
  • Pre-processing and semantic segmentation
  • Object localization and detection
  • Recurrent Neural Networks (RNN)
  • Long-short term memory (LSTM)
  • Syntax and Parsing techniques
  • Statistical NLP and text similarity
  • Text summarization techniques

Projects & Tools

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

Python libraries such as pandas, numpy, scipy, scikit-learn
Visualization libraries such as matplotlib.
Natural language processing libraries such as NLTK
Deep learning packages such as TensorFlow and Keras
Github repositories

You will use these tools to work on three projects spread across:

  1. Neural networks
  2. Computer vision
  3. Natural language processing

You will work on these projects using our GPU-enabled lab that will help you learn and solve problems without buying or installing the computing infrastructure yourself.

Here’s a sample of some of the projects you will be working on as part of this program.

Face Recognition Algorithm (Computer Vision)

Recognize, identify and classify faces within images using CNN and image recognition algorithms.

Fake News Detection (Natural Language Processing)

Explore how sequential models in Deep Learning can be used to distinguish between reliable and unreliable news stories.

This is an indicative sample of the kinds of problems you will solve as part of this program. The faculty are constantly working to expose you to a broad array of scenarios for your coursework.

Learning Outcomes

Learn to use Python, Tensorflow and Keras to develop deep learning applications
Learn to use Python, Tensorflow and Keras to develop deep learning applications
Learn deep learning methodologies to process not only image based datasets but also raw text, numbers etc.
Develop ability to independently solve business problems using deep learning techniques
Develop a verified portfolio with hands on deep learning projects that will showcase the new skills acquired to employers.

Admission Details

Every batch has a limited number of seats and eligible candidates are offered admissions on a first come-first serve basis.

  • We recommend applicants to have 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, probability and exposure to data analysis is preferred.

  • Interested candidates can sign up for the free demo.

  • The Admissions committee will make screening calls to the candidates to understand their background and professional experience in order to assess their candidature.

  • The Admissions Director reviews the screening call discussion and applicant’s profile.

  • Upon approval, admission is offered to the candidate for the upcoming batch. Post payment of admission fee by the candidate, the enrolment is confirmed.


Following are the payment details for the program:


Rs. 1,25,000 75,000 + GST


80+ hours of learning

Hands on projects

Live support sessions

Great Lakes Certificate

GPU accelerated Cloud Lab

Industry sessions


Candidates can pay the program fee through Net banking, Credit Cards or Debit Cards.*

Flexi payment options

Candidates can pay the program fee in 2 equal parts. We also have tie up with various banks that provide an EMI option to candidates.


Mark the Dates


Enrollment Deadline: 18th October 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.

Batch Commencement Date: 10th November 2018

Frequently Asked Questions

Here's a list of the commonly asked questions about the program.

Who will I get the certificate from?

The Deep Learning certificate is awarded by Great Lakes Institute of Management. Please note that certificate for DLCP is not issued by IIT Bombay.

What are the learning support sessions?

Learning support sessions are interactive Q&A sessions conducted live during the course of the program for students to clarify their doubts, and receive guidance on how to advance their project work.

Eligibility criteria?

We recommend the candidates to have at least 2 years of professional experience in a technical role and have basic knowledge of probability, statistics and programming language, preferably, Python. Having said that, we also offer introductory courses on Statistics and python to familiarise the students with.

Who would be teaching in this course?

DLCP is taught by prominent IIT Bombay and Great Lakes faculties and experienced analytics professionals. Access the faculty section for further details.

What is the extent of hands-on exposure? Are there any live projects?

The program includes various hands-on Real-world projects. You will analyse problems using a range of tools & techniques that you have learned in the class. We also offer learning support sessions to help students with their queries on projects.

How does the lab work?

We provide an accelerated computing lab with GPUs and all the relevant tools that you will need to complete your projects. You can access this lab online from anywhere.

Is the content downloadable? How long is the Olympus access available?

No. The content is not downloadable. However, we believe that learning should be continuous and hence, all the learning material in terms of lectures and reading content would be available to you on the LMS even after the completion of the course.

How will I be evaluated during the Program?

DLCP is a holistic and rigorous program and follows a continuous evaluation scheme. Quizzes and experiential learning projects help us evaluate a candidate's understanding of the concepts learned.

Can I pay the fee in instalments?

Candidates do have a provision to pay the fees in 2 equal installments. Further we also have tie-ups with leading banks who provide EMIs for the program. Please contact the admissions helpline at +91 84489 95775 for more details.

What is the application and selection process?
  • All interested candidates are required to apply to the Program by filling up an Online Application Form.
  • Applicants meeting the eligibility criteria receive a screening call from the Admission Director's office
  • Admission Director reviews the screening call discussion and the applicant’s profile.
  • The announcement of results, followed by the release of admission offer letter.
Do I have to attend classes every week?

The program is designed to engage participants every week. All participants are required to learn from videos every week. However, attending leaning support sessions is optional, but recommended. You need to attend it only if you need to clarify your doubts regarding projects.

What if I miss a project submission?

All projects are mandatory and evaluated. If you miss a project, you will not be eligible to earn the certificate.

What are the tools covered in the program?

Python, Keras, Tensorflow, Natural Language Toolkit, Github