Learn modern Data Science live with instructors who actively build and deploy models in industry environments
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Build an AI-assisted churn prediction model to identify users likely to leave a music streaming platform by analyzing engagement and usage patterns. Apply classification techniques to generate early warning signals, user cohorts, and actionable retention insights for product decision-making.
Up to 10 Capstone Projects to choose from
What learners will build:
An AI-powered review intelligence system that ingests thousands of product reviews and produces concise summaries, sentiment breakdowns, and recurring issue clusters for product and marketing teams.
Tools & concepts used:
LLMs for text summarization, sentiment analysis, topic modeling, embeddings for review clustering, prompt engineering, and basic evaluation metrics.
What learners will build:
A pricing decision engine that simulates different pricing and promotion strategies and shows their impact on revenue, conversion, and margins under multiple scenarios.
Tools & concepts used:
Predictive modeling, scenario analysis, optimization techniques, feature engineering, Python-based data modeling, and decision trade-off frameworks.
What learners will build:
A hospital ranking and recommendation system that dynamically adjusts rankings based on user preferences such as cost sensitivity, quality of care, and wait times.
Tools & concepts used:
Multi-criteria decision-making models, weighted scoring systems, normalization techniques, preference modeling, and basic recommendation logic.
What learners will build:
A retrieval-augmented AI assistant that answers medical questions using both structured datasets and unstructured documents, with responses grounded in verified sources.
Tools & concepts used:
Retrieval-Augmented Generation (RAG), vector databases, embeddings, document chunking, prompt grounding, and citation-aware response generation.
What learners will build:
A natural language–to–SQL AI assistant that allows analysts to ask business questions in plain English and automatically generates accurate SQL queries over financial data.
Tools & concepts used:
LLMs for text-to-SQL, schema understanding, prompt templates, query validation, error handling, and database integration concepts.
What learners will build:
A credit approval strategy simulator that evaluates how different approval thresholds affect default rates, revenue, and customer growth.
Tools & concepts used:
Risk modeling, classification models, threshold tuning, ROC/precision-recall analysis, and business-aligned model evaluation.
What learners will build:
An anomaly detection system that scans large-scale security logs to identify suspicious patterns and potential threats in near real time.
Tools & concepts used:
Unsupervised learning, anomaly detection techniques, time-series analysis, feature extraction from logs, and alerting logic.
What learners will build:
A model monitoring and drift-detection framework that tracks security model performance and flags when retraining or recalibration is needed.
Tools & concepts used:
Data drift and concept drift detection, performance monitoring, feedback loops, statistical monitoring, and MLOps fundamentals.
What learners will build:
A virality prediction model that estimates the likelihood of social media content going viral based on early engagement signals.
Tools & concepts used:
Engagement feature modeling, supervised learning, temporal features, classification/regression models, and model evaluation techniques.
What learners will build:
A moderation policy simulator that helps platforms set and test moderation thresholds while balancing safety, free expression, and operational cost.
Tools & concepts used:
Decision modeling, threshold optimization, cost-sensitive learning, policy simulation, and trade-off analysis.
Pre-requisite: STEM background (mandatory) and Coding Experience (good to have).
Learn from 30+ Tier 1 Data Science practitioners, including:
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Step 1: Register for our pre-enrolment webinar.
Step 2: Attend the webinar and understand everything about the program; ask all your questions to our experts during the session.
Step 3: Once you attend the webinar, you will be able to start the enrolment process with the help of our trusted Program Advisors.
Step 4: Our Program Advisors are equipped to help you understand the Data Science Program and how it can help your career growth.
Step 5: Get a 1:1 consultation with them to fast-track your enrollment!
Who is this Data Science program designed for?
This program is built for professionals with a STEM background—engineers, analysts, PMs, consultants, and tech professionals—who want to become job-ready Data Scientists or transition into AI-native data roles. Coding experience is optional.
Do I need prior Data Science or Machine Learning experience?
No. You don’t need prior Data Science or ML experience. The program offers Beginner and Advanced entry tracks, depending on your Python and SQL proficiency.
Is this course live or self-paced?
This is a live, instructor-led program with hands-on sessions, assignments, and project builds. Self-paced content is used only for pre-work and optional reinforcement—not as the core learning format.
How is this different from typical Data Science courses?
Most courses are theory-heavy or tool-focused. This program is execution-first, AI-native, and designed around real 2026 job requirements, with live instruction from practicing industry professionals.
What does “AI-Native Data Science” actually mean?
AI-Native means you’ll learn Data Science the way it’s practiced today—using GenAI tools for coding, analysis, experimentation, and insight generation, alongside classical ML and statistics.
Will I still learn core Data Science fundamentals, or is this just GenAI?
You’ll master core fundamentals first—Python, SQL, statistics, ML, time series, and modeling. GenAI and Agentic AI are layered on top to accelerate workflows, not replace foundational thinking.
What kind of projects will I build?
You’ll complete:
All projects are designed to be resume-ready and interview-defensible.
When do I choose my specialization?
You choose your live specialization after the first 3 months, once you’ve built a strong Data Science foundation and understand your career direction better.
What specializations can I choose from?
You can specialize in:
Each specialization is live, instructor-led, and role-aligned.
How practical is the learning—will I actually code and build things?
Very practical. You’ll code in live classes, complete graded assignments, build models end-to-end, and work on real datasets—this is not a slide-based or demo-only course.
Who teaches the program?
Classes are taught by FAANG+ and senior industry practitioners—Data Scientists, ML Engineers, and AI leaders who actively work on real production systems.
How much time should I expect to spend each week?
Plan for 10–15 hours per week, including live classes, assignments, and project work. The structure is designed to be manageable for working professionals.
Will this program help me with interviews and job transition?
Yes. An optional interview prep track includes:
What roles will I be prepared for after completing this program?
Depending on your background and specialization, you’ll be prepared for roles such as:
25,000+ Professionals Trained
₹23 LPA Average Hike
600+ MAANG+ Instructors
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Join 25,000+ tech professionals who’ve accelerated their careers with cutting-edge AI skills
25,000+ Professionals Trained
₹23 LPA Average Hike 60% Average Hike
600+ MAANG+ Instructors
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Learn about hiring processes, interview strategies. Find the best course for you.
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Explore your personalized path to AI/ML/Gen AI success
Join 25,000+ tech professionals who’ve accelerated their careers with cutting-edge AI skills
Join 25,000+ tech professionals who’ve accelerated their careers with cutting-edge AI skills
Webinar Slot Blocked
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Time Zone: Asia/Kolkata
Hands-on AI/ML learning + interview prep to help you win
Explore your personalized path to AI/ML/Gen AI success
See you there!