Become a job-ready Data Analyst in 12 weeks.

Excel, SQL, Python and Power BI / Tableau taught the way real analytics teams work — clean messy data, run tests, ship dashboards that stakeholders actually use. Placement support with 150+ hiring partners.
0% EMI availablePlacement guaranteeHands-on labs included
Data Analyst Career Track
Only 6 seats left
  • 12 weeks · live mentor-led
  • 60+ hands-on labs with real datasets
  • 3 portfolio dashboards + case studies
  • Weekly 1:1 with your assigned mentor
  • Interview prep: SQL, guesstimates, case rounds
  • Lifetime placement support
  • 30-min call · no pressure · get a personal roadmap
    12 wks
    Cohort length
    60+
    Live labs
    9.4/10
    Alumni rating
    91%
    Placement rate
    Alumni working at
    DNMPramataResponsiveSocial Bytes Pvt LtdUPLDMG
    Outcomes

    What you'll be able to do on day one at your new job

    Every module ends with a graded lab that mirrors what teams actually ship. No slides-only theory.

    Write advanced SQL — CTEs, window functions, ranked partitions — for any BI ask.

    Clean and reshape messy datasets in Excel with Power Query and pivot models.

    Perform EDA in Python using pandas, NumPy, matplotlib and seaborn.

    Design and defend A/B tests, T-tests, ANOVA and confidence intervals.

    Build interactive Power BI dashboards with DAX and RLS.

    Tell a data story that survives an executive review meeting.

    Use LLMs safely to draft code, debug and summarize findings.

    Trace a funnel drop-off end-to-end and propose the fix.

    12-week curriculum

    Seven modules. Business-analyst shaped from day one.

    Get the detailed syllabus PDF
    1. Module 01
      Weeks 1–2

      Data Foundations & Business Analytics (Excel)

      The tool every corporate stakeholder actually opens.

      • VLOOKUP, INDEX-MATCH, XLOOKUP
      • IF, AND, OR, SUMIF, COUNTIF
      • Advanced Pivot Tables & slicers
      • Power Query & Power Pivot
      • Data cleaning & validation
    2. Module 02
      Weeks 3–4

      Relational Databases & Querying (SQL)

      Pull precisely what stakeholders need.

      • SELECT / WHERE / GROUP BY / HAVING
      • INNER, LEFT, FULL OUTER, CROSS joins
      • Subqueries & Common Table Expressions
      • Window functions: RANK, ROW_NUMBER, moving avg
      • DDL/DML: CREATE, ALTER, UPDATE
    3. Module 03
      Weeks 5–6

      Statistical Analysis & Interpretation

      The math that makes numbers defensible.

      • Mean, median, variance, IQR, skewness
      • Box plots, histograms, scatter matrices
      • Probability & Central Limit Theorem
      • A/B tests, T-tests, Chi-square, ANOVA
      • Correlation vs causality, linear regression
    4. Module 04
      Weeks 7–8

      Programming for Analytics (Python)

      Automate the work Excel can't handle.

      • Variables, control flow, functions
      • pandas & NumPy: cleaning, indexing, grouping
      • EDA with matplotlib & seaborn
      • LLM-assisted debugging & summarization
    5. Module 05
      Weeks 9–10

      Data Visualization & BI (Power BI / Tableau)

      Turn observations into stakeholder-ready dashboards.

      • Connections & star-schema modeling
      • DAX & LOD expressions
      • Dynamic KPIs, geospatial maps
      • Publishing, scheduled refresh, RLS
    6. Module 06
      Week 11

      Predictive Basics & Big Data (Add-on)

      Bridge to entry-level ML and modern warehouses.

      • Linear & Logistic Regression with scikit-learn
      • Simple classification models
      • Cloud warehouses: Snowflake, BigQuery, Redshift
      • When to hand off to a Data Engineer
    7. Module 07
      Week 12

      Capstone Portfolio & Interview Prep

      Ship 3 end-to-end business cases.

      • Marketing funnel drop-off analysis
      • Supply chain SQL deep-dive
      • Sentiment tracker with scraped data
      • SQL / case round mock interviews
    Mandatory capstone labs

    Projects you'll actually ship

    Lab 01

    Marketing Funnel Analysis

    Use Excel + Power BI to pinpoint exactly where user conversions are dropping across a 5-step funnel.

    Lab 02

    Product Inventory & Supply Chain Review

    Complex SQL CTEs and window functions to trace regional performance and surface data inconsistencies.

    Lab 03

    Customer Sentiment & Trend Tracker

    Scrape live data, clean text in Python, and present outcomes in an interactive executive dashboard.

    1,200+
    Analysts placed
    150+
    Hiring partners
    8 yrs
    Training experience
    14
    Max cohort size
    Student stories

    Real placements. Real hikes. Real portfolios.

    "I was a non-CS graduate scared of SQL. By week 6 I was writing CTEs in mock interviews. Landed an analyst role with a fintech before the cohort ended."
    A
    Ananya Rao
    Business Analyst · fintech
    ₹9.5 LPA offer
    "The Power BI capstone became the top item on my resume. Recruiters asked to see it before every interview."
    K
    Karan Malhotra
    Data Analyst · e-commerce
    70% hike
    "Mock case rounds were tougher than the real ones. That's exactly what I needed."
    Z
    Zoya Khan
    Insights Analyst · Big 4
    Career switch in 3 mo
    "Weekly 1:1s with my mentor kept me accountable. I would not have finished the capstone otherwise."
    V
    Vishnu Prasad
    Analytics Associate
    First job in analytics
    FAQ

    Everything parents & partners ask

    Do I need a CS or math background?

    No. We start from Excel formulas and ramp up. Any graduate with school-level math can succeed. Half our alumni come from non-technical degrees.

    Is the training online or in-person?

    Hybrid. Weekday sessions online, weekend labs and mock interviews at our Chandra Layout campus in Bengaluru (or fully online for remote learners).

    What datasets will I work with?

    Real anonymized datasets from marketing, e-commerce, supply chain and product analytics teams — not toy CSVs.

    Will I learn Tableau or Power BI?

    Both. Primary focus is Power BI (used by most Indian enterprises) with a 2-week Tableau bridge for consulting/product roles.

    What roles do alumni get placed into?

    Business Analyst, Data Analyst, BI Analyst, Insights Analyst, Product Analyst — with average packages of ₹6-11 LPA for freshers and ₹12-22 LPA for experienced.

    What's the fee and are EMIs available?

    Fee is ₹65,000 all-inclusive. 0% interest EMIs across 6, 9 and 12 months. Scholarships available for women returnees and students from tier-3 cities.

    Next cohort · Aug intake

    Your Data Engineering career starts with a 30-min call.

    Talk to a mentor. Get an honest read on your background, a personalized roadmap, and full fee + EMI details. No pressure.

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