Master the modern data stack – from Python and statistics to LLM-powered analytics, RAG pipelines, and production ML.
6 months
Live cohort + self-paced
Beginner to job-ready
Python, pandas, NumPy, and the data wrangling muscle memory you actually need.
Statistics and probability, taught through code — not Greek letters on whiteboards.
Classical ML: regression, classification, clustering, evaluation done right.
Deep learning with PyTorch, plus the maths only when it matters.
Working with LLMs: embeddings, RAG, evals, and agentic data workflows.
Deploying models and dashboards - not just notebooks.
Every skill is practiced through builds – not slides.
→ Python, Git, Linux basics
→ Statistics & probability through code
→ SQL from zero to advanced joins
→ Regression, classification, clustering
→ Feature engineering
→ Evaluation & metrics that matter
→ Neural nets with PyTorch
→ CNNs, RNNs, Transformers
→ Fine-tuning small models
→ LLM APIs, embeddings, vector stores
→ RAG systems end-to-end
→ Agent workflows for analytics
→ Portfolio capstone
→ Interview prep + mock rounds
→ Resume, LinkedIn, referrals
Build a ChatGPT-style assistant grounded in a real dataset, with evals.
Train, evaluate, and deploy a classification model for transaction fraud.
Time-series forecasts shipped as an interactive Power BI / web dashboard.
An autonomous agent that explores a database and writes its own SQL.
No. We start from absolute basics in Python and ramp up quickly.
Limited seats. Real mentorship. Real outcomes.