Program Overview

GreyAtom is focussed on building full stack data scientists and gives you all the tools, techniques, and core concepts needed to make an impact. The program will enable a learner to apply problem-solving and creative thinking to real-world data sets, gaining experience across the entire data science stack.

Program Outcome

  • Build 4 Production Grade Applications.
  • Be fully Industry ready with projects built on REAL data and strong social presence.
  • Become employable from startups to major tech giants.
  • Build great professional network

Topmost Learning Benefits

  • Practice oriented program
  • 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.

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

Curriculum

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

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

Classification

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

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

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

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

Download the Detailed Syllabus

Elevate your career with GreyAtom Immersive Data Science Engineering Program

Mentors and Instructors

Mayuresh Shilotri

Mayuresh Shilotri

Instructor
Shweta Doshi

Shweta Doshi

Career Coach
Divyesh Shah

Divyesh Shah

Mentor
Paul Meinshausen

Paul Meinshausen

Mentor
jay Trivedi

Jay Trivedi

Instructor
Shweta Doshi

Deepak Angrula

Instructor
Shweta Doshi

Bhumil Haria

Instructor
Shweta Doshi

Soumendra Dhanee

Instructor
Shweta Doshi

Sidharth Ramachandran

Instructor
Kunal Singh

Kunal Singh

Instructor

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

- Bhavesh Bhat

Student Life

8 hours in-Campus

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

Daily Stand Ups

After a 10 minute daily stand up, we'll introduce new concepts.

Recreation

Enjoy tea-coffee, jenga and foosball break!

Industry Lecture

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

Industry Projects

Yatra.com

Predict first international destination for a Tier 2 city customer.

Haptik

Based on Haptik's conversation dataset, benchmark its sentiment.

CCAvenue

Improve the real time visualisation , enabling better & in time decision making

CleverTap

Based on Clevertap dataset , predict which user will uninstall which App next.

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

- Arunabh Singh

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.

Coaching

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 Tools - Commit.Live

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


Learn by Doing

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

Build Strong Habits

Interactive, exercise driven chapters and daily assessment in Commit.Live boosts interest and develops discipline over time.

Stuck? Ask Experts

Ask questions, get answers from experts, peers and professionals in commit.live forum.

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.

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.

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).

Admission

Batch

Weekend - 24 Weeks (Classroom)
Saturday and Sunday

Start Date Location
10th March 2018 Mumbai
13th January 2018 Mumbai

Eligibility

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

After multiple reviews of the applicant pool, our industry partners have chosen to extend support to GreyAtom's Full Stack Program. Please note, scholarship is for limited students applying for January 2018 & March 2018 batches.

Actual Fee - INR 1,70,000/-

Industry Scholarship upto 40% (INR 68,000/-).
You pay the rest.

Interest Free Instalments
Instalment 1 45% during admission.
Instalment 2 55% within 45 days of batch commencement.

* Instalment percentages are liable to change

Discounts
Full payment at the time of admission 5%
Referral Bonus Upto INR 3000

(* Terms and Conditions Apply)

* 18% GST tax applicable on all the above fees