How GreyAtom will transition your career to Data Science
——— Job-ready skills ———
Curriculum built in collaboration with hiring partners and top academicians.
——— Expert mentors ———
Mentors from the industry teach concepts and guid projects.
——— Industry-relevant projects ———
Solve business problems from the industry and test out your practical skills.
——— 1:1 Mentor led session ———
Clear doubts and confusion with mentor to improve your skills and knowledge.
——— Placement assistance ———
Dedicated coaches, mock interviews, workshops and more to establish your career.
——— Portfolio-building ———
Do activities that are essential to building a strong Data Science portfolio.
How you will learn
Learn online with live mentor sessions, attend group study sessions, and interact with top developers and peers offline. Sessions are available in Mumbai, Bengaluru, and Hyderabad. More cities coming soon.
Learner success stories
We invest in each of our learners, ensuring their successful outcomes are
reason is simple: your success is our success.
"The path to me discovering Data Science was long and winding, but thanks to GreyAtom, the journey to becoming a Data Scientist was straightforward."
RM & Operations at Indian Odyssey Pvt. Ltd.
Sr. Associate - Data Science
"I wanted to transition from telecom to data science. Joining GreyAtom, learning from mentors and prep with the career services team made that happen."
Assistant Manager - Network
Assistant Manager - Data Analytics at Nearby Technologies
We have placed over 2500+ learners. Watch a few of our learners talk about their experience at GreyAtom.
Learner success video
Data Science toolkit
- Fundamentals of Python
- Introduction to Git
- Manipulating Data with Numpy
- Data Wrangling using Pandas
- Data Visualization with Matplotlib
Statistical Tools for Data Science
- Summarizing Data with Statistics
- Introduction to Probability
- Making inference from Data
Foundations of Machine Learning
- Make your first prediction with Linear Regression
- Optimizing linear regression models through Regularization
Supervised Machine Learning
- Solving Classification problem using Logistic Regression
- Building the right Decision Trees
Data Preparation for Machine Learning
- Exploratory Data Analysis
- Data Pre-processing Techniques
- Feature Selection Techniques
Practical Machine Learning
- Ensembling Techniques and Random Forest
- Gradient Boosting Machines
- Unsupervised Machine Learning - Clustering
Machine Learning in Production
- Challenges in ML
- Deployment of ML model
- From Business Problem to Data Science Problem
Natural Language Processing
- Introduction to Natural Language Processing
- Analysing Text Data using Sentiment Analysis
Methods of Text Analytics
- Topic Modeling
- Language Models
- Parsing through Text Data
Natural Language Understanding
- Using RASA tech stack to develop Chatbot
- Deep Neural Nets
- Optimizing Neural Nets
Recurrent Neural Networks
- Deep Learning for Text
Solve business problems
Learn concepts through immediate application on real and simulated industry problems. Here are a few of the industry-relevant projects you can expect to work on.
Retail Buyers SegmentationPerform segmentation on customer invoice data of a retail market major to identify clusters of similar spenders.
Customer Complaints ClassificationRoute customer complaints to the right department for the speedy closure of issues.
Sentiment Classification using DLClassify reviews present on IMDB into the right sentiment bucket to quickly help users decide whether to watch the movie or not.
Built and mentored by industry experts, our emerging tech programs have been created to give you a solid foundation for high-growth careers.
Get your dream job with GreyAtom career services
——— 1:1 career counselling ———
Personal sessions with a counsellor to guide you to your successful outcome.
——— 1 mock interview ———
Practise valuable interview skills before attending actual interviews and learn to put your best foot forward with feedback.
——— Career workshops———
Learn what to expect from the industry and how to fit into the workplace with soft skills training to complement your hard skills.
—— Resume and portfolio building ——
Build a digital footprint with a solid personal brand that reflects your value to the industry.
Our alumni work at
Your passport to a successful Data Science career
Share your achievement with recruiters, coworkers, peers, friends and family.
- 6+ Years of Work Experience
- Individuals looking to upskill within the organization
- Individuals with Non-Tech Background
- Freshers or Up to 6 Years of Work Experience
- Individuals with technology understanding
- Individuals looking to transition into Data Science Career