Still building every report by hand in Excel? Companies aren't hiring analysts who calculate — they're hiring analysts who query, automate, and visualize. This is the course that gets you there.
Learn SQL, Excel/Python, and Power BI/Tableau the way working analysts actually use them — building towards a capstone dashboard on a real business dataset, not just a certificate.
By the time you finish this course, you will have queried a real business database in SQL, cleaned and analyzed data in Python, and built a dashboard in Power BI or Tableau that answers an actual business question — end to end. That combination — SQL, Python, and a BI tool — is the baseline almost every data analyst job posting in India asks for right now. This course is how you get there in 8 weeks.
Syllabus
Phase 1: Excel, SQL & Statistics (Weeks 1–4)
Modules
Welcome to Data Analytics
Excel for Analytics
SQL Fundamentals & Joins
SQL Aggregation & Advanced Queries
Descriptive Statistics
Data Cleaning & Data Quality
Applied Lab & Phase 1 Review
Phase 2: Python, Dashboards & Capstone (Weeks 5–8)
Modules
Python for Analytics
Data Cleaning & EDA in Python
Power BI
Tableau
Capstone Project
Full session-by-session breakdown (all 24 sessions, 2-hour format) is in the downloadable curriculum PDF linked from the hero.
Outcome
By the end of this course, you will be able to:
- Write SQL queries to extract, join, and aggregate data from real business databases
- Clean and structure messy datasets in both Excel and Python (pandas)
- Calculate and correctly interpret descriptive statistics on business data
- Build interactive dashboards in Power BI and Tableau that non-technical stakeholders can actually use
- Run exploratory data analysis in Python using pandas, Matplotlib, and Seaborn
- Turn a vague business question into a structured analysis plan
- Present data-backed recommendations — not just charts
- Deliver a capstone project that demonstrates end-to-end analytical capability
- Career roles you'll be ready for: Data Analyst, Business Intelligence Analyst, Reporting Analyst
Tools
Excel
MySQL
Python
Pandas
NumPy
Tableau
Power BI
Jupyter Notebook
Who Should Enrol
Coming from a non-technical background?
No coding experience needed. We start with Excel, and SQL builds naturally from there — you'll be querying real databases within two weeks.
Already comfortable in Excel, want to go further?
Skip straight to what Excel can't do: SQL joins across tables, Python automation, and dashboards that update themselves.
Working in ops, marketing, or finance and drowning in spreadsheets?
Learn the exact tools your company's data team already uses, so you stop waiting on them for every report.
Considering a full switch into data?
This is the on-ramp. Finish here, then go straight into Applied Data Science without repeating a single fundamental.
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FAQs
Beginners, career switchers, and working professionals in non-technical roles (ops, marketing, finance) who want practical data analysis skills — SQL, Excel, Python, and dashboards — without needing a computer science background.
No. The course starts with Excel, and SQL and Python are introduced gradually with labs at every step. If you’ve never written a line of code, you’ll be comfortable by Week 3.
This course covers the tools every data role needs: SQL, Excel/Python fundamentals, statistics, and dashboards. Applied Data Science picks up from here and goes into feature engineering, A/B testing, and machine learning — this course is the prerequisite.
A capstone project analyzing a real business dataset — cleaning it, querying it in SQL, analyzing it in Python, and presenting the findings through a Power BI or Tableau dashboard, with business recommendations.
Each course stands on its own with its own certificate. Data Analytics Foundations is a complete, job-ready skill set by itself — Applied Data Science is there if you want to go further into modelling and experimentation.