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

Program Overview

GreyAtom’s 24-week classroom offering covers core and advanced concepts, techniques, and tools that a data scientist will find handy in aiding decision-making. As you progress through the program, you will build the kind of problem-solving acumen that is needed to resolve real world problems.

Program Outcomes

  • Build 4 production grade applications
  • Be fully industry-ready with projects built on REAL data
  • Solve assignments and quizzes for each module
  • Participate in Hackathons
  • Become employable, from startups to major tech giants

Learning Benefits

  • 24x7 tech support
  • Life-long access to our campus
  • Lifetime access to video lectures
  • Watch lecture videos multiple times
  • Build strong social media presence and 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

Industry Partners

"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

Student Projects

Our students build projects that are modeled on real industry data sets and address real-world challenges. This is part of the Immersive Learning experience of GreyAtom's flagship program. Browse through some of our students' projects to discover the learning outcomes.

View All Projects

Career Services

Our career services work closely with you throughout the program. We help you identify your strengths and weaknesses, determine career interests, and spot employment opportunities. We empower our students to become self-sufficient in navigating the everchanging employment landscape.

Digital Profile Building

At graduation, you will have an extensive and rich GitHub portfolio, several storytelling blogs on Medium, and a résumé that does most of the speaking.

Interview Prep

We help our students develop confidence and become comfortable with job interviews through on-campus training sessions, roleplay, and mock interviews.

Understanding Job Market

Our career coaches help you understand the hiring landscape and navigate its challenging terrain.

Student Life

8 hours in-Campus

40% - Instructor-led lessons.
60% - Coding exercises.

Placement Assistance

Placement Assistance

Bi-weekly sessions on developing soft skills, negotiating salary, and building résumé.


Enjoy tea or coffee, jenga, and foosball!

Industry Lecture

Join your cohort in the evening for a talk by industry speakers.

Our Tool - Commit.Live

Commit.Live™ is our in-house, cloud-based training platform. Integrated with GitHub and Medium blogs, our training platform brings the best of all worlds at the click of a button. With on-board performance analytics and gamification, Commit.Live offers a seamless, immersive learning experience.

Learn by Doing

Learn data science by doing actual work on industry data sets. Commit.Live combines Immersive Learning with real data sets to deliver optimum learning outcomes.

Integration with GitHub

Commit.Live allows users to auto-post their work on GitHub. Over time, it builds a portfolio of demonstrable skills that can be leveraged during job applications.


Users can collaborate with peers on Commit.Live to troubleshoot problems. This leverages one of the key tenets of Immersive Learning - peer-to-peer collaboration.


Commit.Live is a custom variant of GitHub’s Atom text editor, combined with a fully-configured, virtualized terminal. Its integration with Jupyter Notebook allows you to code as you learn.

Real time dashboard

Commit.Live’s embedded analytics reflects the most current information about the user’s performance and assignment scores.

Build storytelling skills

A data scientist should be able to weave a compelling narrative around his work product. Commit.Live’s gamified blogging experience incentivizes users to blog on esteemed portals like Medium.com.



April7 - Oct20

Sat, Sun • 9am-5pm
Start Application

July7 - Feb24

Sat, Sun • 9am-5pm
Start Application


To apply for the Full Stack 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 April 2018 & July 2018 Batches

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

Apply for Scholarship Now

Program Certificate

Users will be awarded a certificate upon the completion of the program. Also, users will enjoy lifetime access to learning materials, assignments, and quizzes.

Starts In

Immersive Data Science Program

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