Foundations of Data Science
Starts May 22 | 4 weeks

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
Earn a certificate with unique credential id
Explore careers in data science
When: May 22 to Jun 18, 2026
Sessions: On weekend evenings, India time
Duration: 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
Structure
May 22 - Session 1: Introduction to Data and Real-World Problems
What data science is, where data comes from, and how data is used to solve real problems in business, society, and science.
May 23 - Session 2: Data Analysis Using Excel
Cleaning, organising, and analysing datasets in Excel using formulas, charts, and basic insights from real data.
May 24 - Session 3: Asking the Right Questions with Data
Framing strong problem statements, choosing the right data, and interpreting results meaningfully.
May 29 - Session 4: Introduction to Python for Data Analysis
Getting started with Python for data analysis, covering basic syntax and working with datasets.
May 30 - Session 5: Project Building Workshop (Excel + Python)
Selecting a project, analysing data, and building initial insights using Excel and Python.
May 31 - Session 6: Project Building Workshop (Insights + Visuals)
Refining analysis, improving visualisations, and strengthening project insights.
June 5 - Session 7: Project Deep Dive - Data Cleaning and Structuring
Cleaning, structuring, and preparing project data for deeper analysis.
June 6 - Session 8: Project Deep Dive - Analysis and Insight Generation
Applying analytical techniques to extract meaningful insights from project data.
June 7 - Session 9: Project Deep Dive - Validation and Storytelling
Validating findings, refining conclusions, and shaping a clear data story.
June 12 - Session 10: Python for Data Analysis - Working with Libraries
Using Python libraries to load, clean, and analyse data more efficiently.
June 13 - Session 11: Python for Data Analysis - Visualisation and Insights
Creating charts and extracting insights using Python-based visualisation tools.
June 14 - Session 12: Python Project Refinement and Presentation
Finalising the project using Python, improving code, visuals, and explanations.
June 18 - Final Project Submission
Final project submission for publishing and certificate award.
