Retail sales analysis
Data Science
Beginner to intermediate
Python for Data Science
Learn Python, SQL, analysis and visualisation from first principles with guided practice every week.
- Duration
- 12 weeks
- Level
- Beginner to intermediate
- Format
- Live online
- Next cohort
- 26 Aug 2026
Overview
What this program covers
A structured foundation in practical data work: Python, data wrangling, statistics, SQL and dashboards, built around weekly datasets and a portfolio-ready capstone analysis.
Who it is for
- College students
- Career switchers
- Analysts
Learning outcomes
- Write clean, analysis-ready Python
- Clean and explore real datasets
- Query data confidently with SQL
- Publish an analytical dashboard
Curriculum
Week-by-week curriculum
Every module pairs a live teaching session with a guided lab and a reviewed deliverable you keep in your portfolio.
Modules
12
Live teaching hours
36 hrs
Guided lab hours
48 hrs
Tools and technologies
Python
NumPy
Pandas
Matplotlib
Plotly
SQL
Power BI
Jupyter
Skills you gain
Python
Pandas
SQL
Visualisation
Statistics
Projects
What you will build
Sample projects from this program. Your capstone can be adapted to your own domain.
Customer churn exploration
Operations KPI dashboard
Cohorts
Upcoming batches
Open
26 Aug 2026
Weekends, 2 live sessions per week (IST evenings)
Seats12 of 30 left
Open
7 Oct 2026
Weekday evenings, 3 live sessions per week (IST)
Seats26 of 30 left
Mentors
Who teaches this program
AR
Ananya Rao
Senior Analytics Manager
Retail analytics team
Demo mentor profile. Builds analytics products and dashboards, and mentors beginners through their first data portfolio.
Python
SQL
Visualisation
- Experience
- 9 years
- Programs
- 1
Teaches: Python for Data Science
View profileLearner feedback
What past learners say
Demo content. The weekly datasets and mentor reviews made the difference — I finished with three analyses I can actually walk someone through.
The labs mirrored the messy datasets I see at work. Within two months of finishing the program I automated our weekly reporting and my manager moved me onto the analytics pod.