Cohort 1 opens June 1, 2026 — Applications are live. 25 seats only. Apply Now — ₹100 →
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Practitioner-Led No Engineering Background Needed Selective Admission

PG Certificate · 6 Months · 25 Seats

Read the numbers.
Ship the answer.

In 6 months, you will have built three live dashboards and completed a full capstone business analysis — data to decision, start to finish, all in one document.

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₹69,000 all inclusive · EMI available · Applications reviewed in 48 hours

Program Fee
₹69,000
All inclusive · No hidden costs
📅 Starts June 1, 2026
🕐 Mon / Wed / Fri · 7–8:30 PM IST
👥 25 seats only
⏱ 6 months · 24 live sessions
Start Application — ₹100 →

₹100 refunded if you are not selected

24Live Sessions
3Live Dashboards
5+BI Tools
6Months
25Seats Only
1Capstone Analysis

Who It's For

Is this program for you?

✓ This program is built for you if:
  • You work with data but rely on others to pull or interpret it
  • You want to read a dashboard critically, not just present one
  • You want to ask better questions of your company's data — without being an engineer
  • You're a student, analyst, or professional who wants to move from intuition to evidence
  • You can commit Mon/Wed/Fri evenings for 6 months
  • You want a portfolio with real published dashboards and case studies
✕ This program is not for you if:
  • You want a full data engineering or data science program
  • You expect a job guarantee at the end
  • You cannot attend live sessions consistently
  • You want to become a machine learning researcher

The Curriculum

Module by module.

Module 01 Data Literacy & Thinking in Numbers Weeks 1–2 · 4 sessions ↓

Most people who "work with data" are actually working with someone else's interpretation. This module builds your ability to go to the source — read a dataset, spot patterns and anomalies, ask better questions.

Session 1: What data literacy actually means — and why most people don't have it
Session 2: Reading a dataset for the first time — where to start, what to look for
Session 3: Descriptive statistics in plain English — mean, median, variance, outliers
Session 4: How to ask a good data question — and why most business questions are badly formed
Google Sheets Excel (advanced) ChatGPT / Claude
Module 02 SQL — Talking to Databases Weeks 3–4 · 4 sessions ↓

SQL is the language that lets you ask questions directly to a database — without waiting for an engineer to pull the data for you. This is SQL literacy for business users — the queries that answer 90% of business questions.

Session 5: What a database actually is — tables, rows, columns, relationships
Session 6: SELECT, WHERE, ORDER BY — getting exactly the data you need
Session 7: GROUP BY and aggregations — summarising data by segment, time, category
Session 8: JOINs explained without jargon — connecting related tables
Google BigQuery DB Fiddle Mode Analytics Metabase
Module 03 Data Visualisation & Dashboard Design Weeks 5–6 · 4 sessions ↓

Numbers without pictures are ignored. Pictures without narrative are decoration. This module teaches you how to turn data into visualisations that make a point — and dashboards that decision-makers actually open.

Session 9: Visualisation principles — what makes a chart good and what makes it misleading
Session 10: Tableau from zero — your first workbook and your first published dashboard
Session 11: Power BI fundamentals — the enterprise-standard BI tool
Session 12: Google Looker Studio — free dashboards in 30 minutes
Tableau Public Power BI Google Looker Studio Datawrapper
Module 04 Python for Business Analysis Weeks 7–8 · 4 sessions ↓

Python is taught here as a productivity tool for analysts. The goal: write scripts that do in 30 seconds what takes 4 hours in Excel. No installation required — everything runs in Google Colab.

Session 13: Python basics in one session — variables, functions, loops (the only three things you need)
Session 14: Pandas — reading, cleaning, and transforming data in Python
Session 15: Matplotlib and Seaborn — generating charts from code
Session 16: Automating a real Excel task with Python — the session that saves you hours every week
Google Colab Pandas Matplotlib Seaborn
Module 05 Business Intelligence in Practice Weeks 9–20 · Remaining sessions ↓

How BI actually works inside a company. How to define KPIs that actually matter. How to present analysis to a CEO who has 5 minutes. How to make a recommendation that gets acted on.

Session 17: The data stack in a real company — how data moves from product to dashboard
Session 18: KPI frameworks — choosing metrics that matter, not metrics that are easy to measure
Session 19: Data quality and governance — what to do when the numbers don't add up
Sessions 21–24: Capstone analysis — scoping, building, reviewing, presenting

Apply for Cohort 1

25 seats. June 1, 2026.

Applications reviewed within 48 hours. ₹100 application fee — refunded if you are not selected.

Start Application — ₹100 →