Data Analytics with Python, SQL and Power BI (Data Analytics): From Excel to Dashboards

Learn data analytics live: Excel, SQL, Python with Pandas, statistics, Power BI dashboards, storytelling and a portfolio project; the complete path to a data analyst job.

Live batches with a trainer · Level: Beginner · Duration: 50 hours · Language: English · Fee: ₹19,999

About this course

Data analyst is the most hired entry role in data: every company needs people who can pull data with SQL, clean and analyse it in Excel and Python, build dashboards in Power BI and explain what the numbers mean. This course is the complete path from Excel to a portfolio that gets interviews.

The course starts with how analytics works in a business and advanced Excel (lookups, pivot tables, Power Query), then SQL from basics to window functions on PostgreSQL and MySQL, and Python with Pandas for cleaning, analysis and charts. You then learn the statistics an analyst uses (distributions, sampling, hypothesis tests, A/B tests, correlation and regression) and build dashboards in Power BI: Power Query, data models, DAX measures, visuals, drill-through, row-level security and publishing, with a Tableau overview.

You then practise the analyst's craft: defining KPIs, exploratory analysis, cohort and funnel analysis, forecasting basics, data storytelling and presenting to stakeholders, with an overview of generative AI tools for analysts. The course ends with two portfolio projects (sales and marketing, HR or finance) and preparation for analyst interviews, SQL tests and case rounds. Every topic is done live on real data sets, and every session is recorded.

What you will learn

  • Use advanced Excel: lookups, pivot tables, Power Query and what-if analysis
  • Write SQL from basics to joins, subqueries, CTEs and window functions on PostgreSQL and MySQL
  • Clean, analyse and chart data in Python with Pandas, Matplotlib and Seaborn
  • Apply the statistics an analyst needs: distributions, sampling, hypothesis tests, A/B tests, correlation and regression
  • Build Power BI dashboards: Power Query, data models, DAX measures, visuals, drill-through, row-level security and publishing
  • Define KPIs and run exploratory, cohort and funnel analyses
  • Tell a data story and present findings to stakeholders
  • Use generative AI tools for analysts responsibly
  • Finish two portfolio projects and prepare for analyst interviews, SQL tests and case rounds

Requirements

  • No programming experience needed; comfort with Excel helps
  • Best suited to freshers and graduates (B.Com, BBA, MBA, engineering, science), MIS and reporting staff and professionals moving to data roles
  • A laptop with a stable internet connection (8 GB RAM is enough; cloud notebooks are used for heavy work)

Syllabus

  • Module 1: Analytics in a business (2 hours)
  • Module 2: Advanced Excel (6 hours)
  • Module 3: SQL (10 hours)
  • Module 4: Python with Pandas (10 hours)
  • Module 5: Statistics for analysts (6 hours)
  • Module 6: Power BI (10 hours)
  • Module 7: The analyst's craft (4 hours)
  • Module 8: Portfolio projects and interviews (2 hours)

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