Data Science

Data Science Masters Program

In Association with GreyAtom School of Data Science

Program Overview

 The Data Science Masters Program will turn you in a Machine Learning Pro. Complete with hackathons and guided projects, this program gives you a firm grounding in Machine Learning – from basics to applications.

Program Outcomes

By the end of this program, you will be able to use Python for Data Science, summarize data for analysis, solve problems, implement, evaluate and productionize solutions to data science problems by building appropriate machine learning models and algorithms.



Python Toolkit for Data Science

  • Getting Started with Python
  • Handling Program Flow in Python
  • Manipulating Data using NumPy
  • Data Wrangling with Pandas
  • Data Visualization with Matplotlib

Foundational Machine Learning

  • Summarizing Data with Statistics
  • Introduction to Probability
  • Making inference from Data
  • Make your first prediction with Linear Regression
  • Regularization

Tech Stack

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Machine Learning

Supervised Techniques

  • EDA and Data Pre-processing
  • Machine Learning: Logistic Regression
  • Improving your model with Feature Selection
  • Decision Tree

More Supervised, Unsupervised Machine Learning Techniques

  • Ensembling and Random Forest
  • Gradient Boosting Machines
    Hackathon # 2
  • Machine Learning: Clustering/ k-means
  • Challenges in Machine Learning
  • Support Vector Machines

Working with Text Data

  • Foundations of Text Analytics
  • Topic Modelling on Text
  • Sentiment Analysis using NLP
Hackathon # 3

NLP Project – Haptik -Given a customer query, classify it correctly as sarcastic or non-sarcastic


Deploying ML @ scale

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

  • Pillars of Machine learning deployment
  • Ways to deploy Machine learning Modules.
  • Deploy a docker API in cloud

Tech Stack


Road to Career & Projects

Capstone projects will enable you to apply what you have learned during the program. You would be analyzing a business case study and recommend a solution for the same. Some examples of capstone projects are

  • 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 given a user, when will he do his next balance recharge

Industry Partners


Divyesh Shah

Engineering Manager – Marketplace Management at Uber

Paul Meinshausen

Data Scientist @ Montane Ventures

Mayuresh Shilotri

Indian Institute of Technology, Madras

Jay Trivedi

Data Scientist | IIM Ahemdabad | IIT Roorkee

Deepak Angrula

Indian Institute of Technology, Bombay

Mehul Chopra

Fr conceicao rodrigues college of engineering

Rohit Ghosh

Indian Institute of Technology, Bombay

Soumendra Dhanee

Institute of Mathematics and Applications

Bhumil Haria

Senior Software Engineer at Paycraft

Sudhanshu Saxena

Big Data – Hadoop Trainer, Data Scientist, Big Data Speaker

Manish Kukreja

Data Scientist at Auckland DHB

Avinash Ahuja

Data Scientist @ LinkedIn

Industry Partners

Career Services

Our experienced career services team will help you optimize and amplify your professional presence and help you draw more eyeballs.

Resume Building

Optimize your resume to match job filters for data science positions.

LinkedIn Presence

Learn clever hacks to improve visibility of your LinkedIn profile and get noticed by employers.

Interview Videos

Find out how to answer critical interview questions that make or break the deal.

Student Life

7 hours in-Campus

40% – Intructor led session with hand on coding on real datasets.
60% – Coding exercises.

Career Services

Learn some of the clever hacks to bump your resume and social profile to the top of the pile.


Enjoy tea or coffee, jenga, and foosball!

GreyAtom Learning Platform

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

Learn by Doing

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

Integration with GitHub

GreyAtom Learning Platform 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 GreyAtom Learning Platform to troubleshoot problems. This leverages one of the key tenets of Immersive Learning – peer-to-peer collaboration.


GreyAtom Learning Platform is a fully-configured, virtualized terminal. Its integration with Jupyter Notebook allows you to code as you learn.

Real time dashboard

GreyAtom Learning Platform’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. GreyAtom Learning Platform’s gamified blogging experience incentivizes users to blog on esteemed portals like

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