Diploma in
Data Science
Join the program and get the opportunity to learn under the guidance of a Diploma In Data Science specialist.
Join the program and get the opportunity to learn under the guidance of a Diploma In Data Science specialist.
Data science is more than models—it’s asking sharp questions, cleaning messy data, choosing the simplest method that works, and explaining results clearly. This diploma blends classical data science (statistics, experimentation, modelling, evaluation) with Gen-AI practices (prompt design, retrieval workflows, human-in-the-loop checks). You’ll move from fundamentals to project delivery through short primers, guided demos, and repeatable labs. Every unit ends with an artefact you can reuse: a cleaned dataset, a feature plan, a model report, or an evaluation note. The focus is employability—clear reasoning, measured results, and a portfolio reviewers can trust.
Frame business problems as measurable questions and select the right methods.
Clean and organise data; document assumptions so analyses are auditable.
Engineer informative features and compare models using disciplined validation.
Communicate results with compact visuals and defensible metrics (not vanity scores).
Design Gen-AI workflows that are safe, monitored, and grounded in actual data.
Draft lightweight delivery docs—diagrams, checklists, and “next-step” notes hiring teams expect.
Students/freshers aiming for data/analyst roles with proof of work.
Working professionals in operations, finance, marketing, HR, or IT who need data-driven decisions.
Career switchers seeking a structured path from spreadsheets to analysis and modelling.
Founders/managers who want to evaluate and deploy small, reliable data/AI solutions.
10 modules + capstone, built for practical skill building.
Indicative ranges – vary by city and domain.
Cleaning, exploration, dashboards, decision notes.
KPI tracking, experiments, weekly reporting.
Feature plans, baselines, evaluation discipline.
Prompt libraries, retrieval designs, review checklists.
| Role | Fresher (0–1 yr) | Experienced (2–5 yrs) |
|---|---|---|
| Data Analyst | ₹3.2–5.8 LPA | ₹7–12 LPA |
| Business/Operations Analyst | ₹3.0–5.5 LPA | ₹6.5–12 LPA |
| ML/AI Associate | ₹3.6–6.5 LPA | ₹8–15 LPA |
Explain → Demo → Do → Reflect. Each unit ends with a reusable artefact.
Graduate with: cleaned dataset + dictionary, feature plan, evaluation report, decision note, and optional Gen‑AI helper.
Keep a short log (assumptions, choices, results, next step) – doubles as interview material.
Earned through labs, a midterm mini‑project, and a capstone – assessed with clear rubrics.
Role mapping so your applications align with your strengths and portfolio.
Resume/profile edits that emphasise measurable outcomes (not tool lists).
Mock interviews with feedback you can act on immediately.
Targeted referrals and guidance that continue until you land a role.
Hands‑on first: every topic ends with a lab; each lab feeds your portfolio.
Decision‑focused: we teach why a method fits a target, not just how to run it.
Transparent rubrics: scoring criteria are shared upfront; expectations are concrete.
Portfolio proof: you leave with artefacts that hiring teams can verify in minutes.
Ongoing support & accessible plans: placement help continues until you land a role, with affordable fees, tutorial access, and a welcome kit on day one.
We set you up to start strong—no trick filters.
Align goals, background, weekly capacity, and target roles.
Short, friendly check of quantitative basics – to personalise your start.
Paperwork, portal access, orientation checklist, and first practice dataset.
Build a clean analysis template, log assumptions, run a tiny baseline.
Month‑by‑month map with quality bars and “meets/exceeds” examples.
Once capstone and artefacts meet rubrics, start interview sprints and role‑matching.
Get personalized guidance on courses, scholarships, and career roadmap.