Full Stack Data Science Engineering Program
FULL TIME | Weekend - 24 weeks (Classroom)
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.
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
Build strong foundations on statistical concepts, setup machine and tech fundamentals
Build strong foundations on statistical concepts and perform analysis with real world data sets in python and its associated libraries
Master the art of collecting, extracting, querying, cleaning, and aggregating data for analysis
Develop a deep understanding on real world applications of Supervised ML algorithms.
Solve real world data science problems on industry data sets using appropriate Supervised ML models and algorithms.
Develop a deep understanding on real world applications of Unsupervised ML algorithms.
Understand how distributed systems and parallel computing technologies are solving these challenges.
Productize your data science models. Build a fluid understanding on how to deploy data science products.
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
Multiple capstone projects at GreyAtom have helped me develop my skills on Big Data and all other elements of Data Science.
- Bhavesh Bhat
40% - Instructor and demo hours.
60% - Coding hours
After a 10 minute daily stand up, we'll introduce new concepts.
Enjoy tea-coffee, jenga and foosball break!
Gather with your entire class for an evening lecture by industry speaker.
It’s been an amazing experience gaining knowledge of all the important topics of Data Science. Excellent work done on Commit.Live.
- Arunabh Singh
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.
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.
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.
Commit.Live™ is an in-house cloud-based training platform. It measures metrics like code efficiency, logic, speed etc.
Weekend - 24 Weeks (Classroom)
Saturday and Sunday
Start Date | Location |
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10th March 2018 | Mumbai |
13th January 2018 | Mumbai |
28th October 2017 | Mumbai |
29th July 2017 | Mumbai |
13th May 2017 | Mumbai |
To apply for the Full Stack Data Science Engineering program, you must have
Minimum eligibility criteria may be waived for exceptionally qualified candidates.
Common Process
If chosen for Scholarship
Once an approval is received for scholarship from the industry partner, candidates are emailed an admission decision.
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.
Interest Free Instalments | |
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Instalment 1 | 45% during admission. |
Instalment 2 | 55% within 45 days of batch commencement. |
* Instalment percentages are liable to change
Discounts | |
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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