Data Science 360: Analytics, ML & AI

Data science uses statistics, programming, and machine learning to extract insight from data and build predictive models. It extends data analytics with modelling, deep learning, NLP, computer vision, and deploying models to production.

Data analytics mainly describes and explains what happened using queries, reports, and dashboards. Data science adds prediction and automation — building machine learning models, evaluating them, and deploying them. Data Science 360 covers both, from statistics and SQL through ML, deep learning, and MLOps.

Working knowledge of algebra, statistics, and some linear algebra and calculus helps. The program includes a dedicated Mathematics for Data Science part covering these, so you do not need to arrive already knowing them.

You'll learn: Statistics, experiments and regression on real business data; Explainable machine learning with fairness checks and model cards; Deep learning, NLP and retrieval-augmented generation (RAG); Deploying and monitoring models with FastAPI, Docker and MLflow.

This course covers: Python (pandas, NumPy), SQL (DuckDB, PostgreSQL), scikit-learn, XGBoost/LightGBM, SHAP, statsmodels / SciPy, PyTorch, Hugging Face, Chroma / FAISS + LLM APIs, FastAPI, Streamlit, Docker, MLflow, Evidently, GitHub Actions, Power BI (one module), Claude / ChatGPT / Copilot.

This is a advanced-level course, so it assumes some prior familiarity with the subject.

The course is designed to be completed in approximately 20 weeks, depending on your pace.

Live Class (₹24,999) — Instructor-led live cohort with doubt-clearing sessions — earns both the course and internship certificates (included). Recorded Batch (₹12,999) — Full recordings of a completed live batch — earns both the course and internship certificates (included). Internship Track (₹2,999) — Defined project-based internship track; deliverables and review schedule confirmed before payment. Self-Paced (₹3,499) — Learn anytime with the full recorded curriculum and community access.

Yes — enrolling in the Internship track (or the Live/Recorded tracks, which include it) means working through real projects with our team and earning a separate Internship Certificate, in addition to the course completion certificate for Live/Recorded enrollments.

Yes. Self-paced enrollment earns a course completion certificate once your final project is reviewed and approved. Internship enrollment earns an internship certificate once your internship projects are approved. Live and Recorded enrollments earn both. Every certificate is publicly verifiable on our website and can be added directly to your LinkedIn profile. Certificates are included with Live and Recorded enrollments; for other options, earning a certificate is free and releasing it to view, download and share is a one-time ₹100 fee per certificate.

You'll work on real projects such as: Capstone: Explainable credit-risk decisioning service — KaasuFlow wants to raise approvals without raising losses; build a default model, pick a business-optimal cut-off and serve it with reason codes; Capstone: Customer-voice intelligence assistant — Leadership needs to know what borrowers complain about and to answer policy questions consistently; build complaint triage plus a cited RAG assistant; Data audit + EDA notebook and a tested feature-building module (SQL + Python) in the repo; Experiment readout + interpretable regression notebook with a written decision memo; Published portfolio-risk dashboard (Power BI or Streamlit) + one-page credit committee summary; Credit-default model repo: pipeline code, MLflow experiment log, model card with explanations and fairness results.

Yes — every enrolled student gets full access to our placement support: resume building, a shareable project portfolio, mock interview preparation, and guidance applying what you've built to real job applications. This is support and access, not a guaranteed job outcome — how quickly it leads to an offer depends on the market and your own effort.