5 Modules
176 hrs Instructor Session
208 hrs Assignments Solving
19 Projects
5 Industry Problems

Program Overview

GreyAtom is focussed on building industry-ready data scientists. You will learn all the techniques, core concepts and use of data science tools needed to make an impact as a Data Scientist. This Program will enable you to develop your Problem Solving intuition which you can apply on Real World problems. You will get a hands on Experience in Data Science.

Program Outcomes

  • Build 4 Production Grade Applications
  • Be fully Industry ready with projects built on REAL data
  • Solve assignments and quiz for each module
  • Participate in Hackathons
  • Become employable from startups to major tech giants

Learning Benefits

  • 24x7 tech support
  • Access to our campus is 24x7 and even after you graduate
  • Lifetime access to video lectures
  • Re-attend lectures multiple times if concepts not clear.
  • Build strong social presence and a great professional network

The culture at GreyAtom is excellent and has helped me gain hands on experience in Data Science. It has been a perfect deal for me

Ronak Talreja
Data Science Program, Data Scientist @The Data Team


35%Machine Learning
20%Big Data

Refresher and Launch

Build strong foundations on statistical concepts, setup machine and tech fundamentals

  • Introduction to Data Science
  • Problem Classification
  • Commit.Live Setup
  • Tech Basics

Python and Maths Refresher

Build strong foundations on statistical concepts and perform analysis with real world data sets in python and its associated libraries

  • Basic Python Programming constructs
  • Functions and OOP in Python, NumPy basics
  • Learn Pandas basic concepts, work with Series
  • Work with Pandas DataFrame (Advanced)
  • Working with Visualizations

Tech Stack

git github Commit.live Python Mysql
35%Machine Learning
20%Big Data

Exploratory Data Analysis & ML Workflow

Master the art of collecting, extracting, querying, cleaning, and aggregating data for analysis

  • Introduction to Machine Learning
  • Descriptive Statistics
  • Inferential Statistics
  • Exploratory Data Analysis
  • Machine Learning Workflow
  • Linear Regression

Regression / Time Series

Develop a deep understanding on real world applications of Supervised ML algorithms.

  • Advanced Linear Regression
  • Feature Engineering
  • Feature Selection
  • Logistic Regression
  • Decision Trees


Solve real world data science problems on industry data sets using appropriate Supervised ML models and algorithms.

  • Decision Trees
  • Conditional Trees
  • K nearest neighbour
  • Ensemble Techniques
  • Random Forest

Clustering, NLP & more

Develop a deep understanding on real world applications of Unsupervised ML algorithms.

  • Challenges in Machine Learning
  • Clustering/ k-means
  • Natural Language Processing
  • Deeper into NLP
  • Demo Day

Tech Stack

Matplotlib scipy numpy scikit-learn nltk
35%Machine Learning
20%Big Data

Big Data Ecosystem

Understand how distributed systems and parallel computing technologies are solving these challenges.

  • Introduction to Big Data & Hadoop Ecosystem
  • HDFS architecture
  • HiveOL
  • Pig
  • Spark
  • Sqoop

Tech Stack

hadoop apache-hbase hive spark
35%Machine Learning
20%Big Data

Deploying ML @ scale

Productize your data science models. Build a fluid understanding on how to deploy data science products.

  • Deploying Data Science products
  • Actual Deployment to AWS
  • Parallelization/ Multi-Threading/ Object Orientedness/ Documenting Experiments
  • Intro to H2O

Tech Stack

35%Machine Learning
20%Big Data

Road to Career & Projects

Outlier Detection - Haptik caters to limited number of services. Users tend to ask queries, out of scope of Haptik’s reach. To identify these queries as outliers and handling those by gentle denial is the best practice.

Prepare a model which predicts
a) Given a user , when will he do his next balance recharge

Tech Stack

yatra Haptik CCAvenue CleverTap mmsind flytxt The Data Team HDFC Life

Download the Detailed Syllabus

Elevate your career with GreyAtom Immersive Data Science Engineering Program

Instructors, Mentors & Career Coach

Mayuresh Shilotri

Mayuresh Shilotri

Indian Institute of Technology, Madras
jay Trivedi

Jay Trivedi

Data Scientist | IIM Ahemdabad | IIT Roorkee
Deepak Angrula

Deepak Angrula

Indian Institute of Technology, Bombay
Bhumil Haria

Bhumil Haria

Senior Software Engineer at Paycraft
Sudhanshu Saxena

Sudhanshu Saxena

Big Data - Hadoop Trainer, Data Scientist, Big Data Speaker
Mehul Chopra

Mehul Chopra

Fr conceicao rodrigues college of engineering
Rohit Ghosh

Rohit Ghosh

Indian Institute of Technology, Bombay
Soumendra Dhanee

Soumendra Dhanee

Institute of Mathematics and Applications
Sidharth Ramachandran

Sidharth Ramachandran

Indian Institute of Management, Kozhikode
Divyesh Shah

Divyesh Shah

Engineering Manager - Marketplace Management at Uber
Paul Meinshausen

Paul Meinshausen

Data Scientist @ Montane Ventures
Shweta Doshi

Shweta Doshi

Co-Founder @ GreyAtom - Head - Strategic Partnerships

“We also bring in a lot of Hiring Challenges and conduct Hackathons from our Industry partners to the classroom”

Our prime objective to provide our students with hands on experience in solving data science problems. For this we need a set of world class instructors having a perfect blend of both industry as well as academic experience. And hence we have built a pool of instructors varying from academicians from IIT to Data Scientists at companies like Haptik, Uber etc. We also bring in a lot of Hiring Challenges and Hackathons from our Industry partners to the classroom which develop various of skill set in our students.

Apart from that we have a dedicated team for Learning and Development which will help you with Job search and career opportunities even after the program. Our instructional staff conducts mock interviews, training exercises and role-play sessions designed to help you tackle the job interview.

Multiple capstone projects at GreyAtom have helped me develop my skills on Big Data and all other elements of Data Science.

Bhavesh Bhat
Data Science Program, Data Scientist @HDFC Life

Student Life

8 hours in-Campus

40% - Instructor and demo hours.
60% - Coding hours

Placement Assistance

Placement Assistance

Conduct bi-weekly sessions to train students on soft skills, salary negotiation and resume building.


Enjoy tea-coffee, jenga and foosball break!

Industry Lecture

Gather with your entire class for an evening lecture by industry speaker.

Industry Projects

It’s been an amazing experience gaining knowledge of all the important topics of Data Science. Excellent work done on Commit.Live.

Arunabh Singh
Data Science Program, Data Scientist @The Data Team

Career Services

Count on our career services to work closely with you from day 1 of the program to day 1 of your Job!They will help you identify your strengths and career interests, help you refine your career goals, and identify opportunities for you to connect with hiring partners.

Online Presence

By graduation, you will have a strong, unique Github portfolio, online profiles and a resume that reflects your value in the job market.


Our instructional staff conducts mock interviews, training exercises and role-play sessions designed to help you tackle the job interview.

Student Success Team

Dedicated Team who will ensure to help you with Job search and career opportunities even after the program. Our centre is open for our Alumni 24*7.

Our Tool - Commit.Live

Commit.Live™ is our in-house cloud-based training platform. Integrated with various data science tools it brings everything under one roof to make your learning more efficient. It measures metrics like code efficiency, logic, speed etc. and gamifies your experience with its highly competitive dashboard.

Learn by Doing

Commit.Live ™ is an in-house cloud-based training platform. It measures metrics like code efficiency, logic, speed etc.

Deep Integration with GitHub

GitHub integration enables Commit.Live to auto-push student assignments to GitHub. This builds a transparent and demonstrable portfolio for prospective employers.

Stuck? Ask Experts

Ask questions, get answers from experts, peers and professionals in commit.live forum. Get 24x7 tech support through various mediums like slack, whatsapp or call.

Use Real Data Scientist's Tools

Commit.Live is a custom variant of GitHub’s Atom text editor combined with a fully-configured, virtualized terminal. Students are on the go in minutes. Its integration with Jupyter Notebook helps you to code as you learn. You don’t need to go anywhere out of Commit.Live, it brings all your learning to one place.

Personalised Dashboard

All the metrics like code efficiency, logic, number of attempts, time taken, speed etc. are measured and shown on your dashboard. Earn and lose points for assignments you solve and know where you stand with leaderboard.

Build Social Presence

Blog post is mandatory on completion of a module. It provide prospective employers with greater insight into a student’s skills and mentality. Top posts are shared with the DataGiri (Data science community).



Jan13 - Aug24

Sat, Sun • 9am-5pm
Start Application

March10 - Oct20

Sat, Sun • 9am-5pm
Start Application


To apply for the Data Science Engineering program, you must have

  • A Bachelor’s / Master’s degree (B.E., BCA, MCA, B.Sc, M.Sc, Ph.D.) in a discipline with a strong quantitative component like Mathematics / Physics / Statistics / Economics
  • Applicants with coding experience will be preferred

Minimum eligibility criteria may be waived for exceptionally qualified candidates.

Admission & Scholarship

How to Apply?

Selection Process

Common Process

  • Upon Review (ensuring your fitment to the Program), you will receive an invitation for personal interview.
  • Personal Interview with a panel comprising of Data Scientist and Full Stack Engineers will assess the candidate.
  • Once basic competence in engineering discipline is assessed, learnability, attitude are tested.

If chosen for Scholarship

  • Applicant need to clear above said process.
  • This would be followed by an interview with our Industry Partner.

Once an approval is received for scholarship from the industry partner, candidates are emailed an admission decision.

Fee Structure

Program Fee


  • Scholarship available for limited students
  • Flexible EMI options
  • Discounts on full payment
  • Referral Bonu of upto INR 3000 T&C Apply

Industry Scholarship January 2018 & March 2018 Batches

Industry is not just looking for you but supporting too. Support for limited students only.

Apply for Scholarship Now

Industry-Trusted Immersive Data Science Program Certificate

You earn an industry-trusted program Certificate once you complete the program - even if you finish the program after the official end date. In other words, as long as you have enrolled in the program you will always be able to finish it and to get a program certificate. You will also have permanent access to the program material, your answers and the discussions.

Starts In

Immersive Data Science Program

Weekend - 24 weeks (Classroom) | Sat, Sun • 9am-5pm