Foundations of Data Science
Starts: Aug 29 | 24 hours commitment | ₹ 36,000 | Age 14+
What you'll learn
This Foundations of Data Science Program introduces high school students to real-world problem solving using data. Students learn to analyze data with Excel, explore Python basics, and turn insights into clear stories. The program emphasizes hands-on learning, culminating in one strong, publishable data science project.
Instructors:
Swaroop Reddy
Blockchain Researcher, IIT Hyderabad
Dhruvang Choudhari
Crypto Research Analyst, AMINA Bank
Devesh Lathi
Founder, Futurowise.com
Outcomes
Learn the basics of data science
Create a data science project on a practical world issue
Get published on Futurowise. See what past students have built
Earn a certificate with unique credential id
Explore careers in data science
Details
When: Aug 29 to Sep 8, 2026
Duration: 2 weeks | Live sessions on weekend evenings, India time
Commitment: 24 hours: 12 sessions of 1-hour each + 12 hours of self-paced work
Where: Online (on Zoom)
Recommended For: Age 14 years and above
For students interested in:
STEM, Business, Coding
Overview
Before the program
A short pre-read on data science fundamentals is shared before Aug 29. Students arrive knowing what data science is and why it matters, so live time goes straight into doing.
Week 1 - August 29 and 30 | Data, Excel, and Dashboards (6 sessions)
Session 1
Introduction to data science and problem statement. What data science is and how it solves real problems. Students frame their problem statement and identify their raw dataset.
Session 2
Excel for data analysis and visualisation basics. Cleaning and organising data, applying formulas, and building initial charts.
Session 3
Tableau and Power BI. Building dashboards that tell a clear visual story from your data.
Session 4
Tableau and Power BI deep dive. Advanced dashboard techniques applied to each student's own dataset.
Session 5
Python intro. Syntax, pandas, and loading data. Students set up their environment and run their first analysis.
Session 6
Python data cleaning and analysis. Working with real data, handling missing values, and generating initial findings.
Week 2 - September 5 and 6 | Python, Insights, and Publishing (6 sessions)
Session 7
Python visualisation with matplotlib and seaborn. Generating charts directly from project data.
Session 8
Python project deep dive and insight generation. Students push their analysis further and identify the key story in their data.
Session 9
Final project visualisation and dashboard polish. Bringing together Python outputs and dashboard work into a cohesive, publish-ready visual.
Session 10
Advanced Tableau and Power BI. Refining and elevating the dashboard component of the project.
Session 11
Problem statement refinement and data check-in. Students revisit their original question, tighten the framing, and confirm the data supports their conclusions.
Session 12
Report structure, data storytelling, and publishing. Writing methodology, structuring the report, citing sources, and submitting a polished project on Futurowise.
After the program
Students receive a curated reading list covering data science, Python, and analytics, drawn from resources that practitioners and students actually use. Support is available to help finalize and polish the project report before submission.
The cohort size being small made the meetings very interactive which I really liked about this program. Moreover, I enjoyed researching for the project given to us, which were then very well evaluated and we were given valuable feedback about the real-world applicability.
Anwita
Jamnabai Narsee School, Mumbai