What students actually become here
This is not a shallow “AI awareness” program. Students learn how a real sports-tech problem can be broken down into users, data, logic, interface, and business value — then turned into a working MVP.
Product Thinking
Students define users, pain points, MVP scope, and feature priorities instead of jumping blindly into code.
Data + Scouting Logic
Students create player-impact formulas, shortlist logic, and ranking workflows using match and tournament data.
MVP Building + Demo
Students build a Streamlit prototype, present it, and defend its value like a junior startup or product team.
Program Value Projection
Program Weightage
The curriculum is balanced so students leave with real product understanding, a working build, and a presentable final artifact.
30% Product Thinking
Users, pain points, problem framing, MVP scoping, and wireframing.
35% MVP Build
Python basics, Streamlit, score ingestion, match logic, tournament rankings.
15% AI Insight Layer
Scouting notes, plain-English summaries, and explanation-first AI usage.
20% Pitch & Business
Go-to-market thought, business value, demo storytelling, and final presentation.
The 3-Phase Program Lifecycle
A structured path from understanding the problem to building and pitching the MVP.
Understand & Design
Students decode Khel.ai, define users, identify pain points, build problem statements, and map MVP scope with data logic.
Build
Students create a Streamlit app that processes score data, computes awards, ranks players, and generates shortlist outputs.
Present
Students prepare business positioning, polish the interface, build the pitch deck, and present their product in a final demo day.
What the final MVP must do
The final student project is a Tournament Scouting Assist MVP. It takes tournament score data and turns it into meaningful match awards, rankings, and scouting support outputs.
Inputs
Tournament name, player names, roles, jersey number, and match-wise stats like runs, wickets, overs, and fielding events.
Outputs
Man of the Match, Tournament MVP, role-wise rankings, Top 5 players to watch, and short scouting explanations.
Logic Layer
Students build impact formulas for batting, bowling, and all-round performance with fairness discussions included.
AI Layer
Optional AI generates plain-English scouting notes and tournament summaries after the rules engine produces rankings.
Final MVP Output Mix
15-Day Delivery Plan
Each day ends with something visible: a note, a map, a formula, a wireframe, a module, or a final presentation asset.
Welcome to Khel.ai and AI Products
Reflection on Khel.ai, AI, and project expectations.
Users, Buyers, and Product Problems
User map plus top 5 pain points in cricket and tournament workflows.
Problem Statements and Opportunities
Students write a sharp problem statement and choose a product angle.
What Makes a Good MVP?
Students split must-haves from nice-to-haves and define scope clearly.
Data Thinking for Cricket Products
Students build a data dictionary and sample match dataset.
Ranking Logic and Fairness
Students create impact formulas and discuss fairness, bias, and context.
Product Flow and Wireframing
Students create user flow diagrams and low-fidelity wireframes.
Python and Streamlit Kickoff
Students run starter code and display tournament data in the app.
Match-Level Calculations
Students compute match outcomes and build Man of the Match logic.
Tournament-Level Rankings
Students aggregate multiple matches into leaderboards and shortlist outputs.
Add the AI Layer
Students use AI for scouting-note generation and plain-English insights.
Dashboard, UX, and Product Polish
Students improve usability, add charts, and refine the interface.
Business Thinking and Go-To-Market
Students connect the MVP to customer value, pricing thought, and adoption logic.
Pitch Deck and Demo Preparation
Students prepare the final pitch deck, demo flow, and storytelling sequence.
Demo Day and Showcase
Students present the app, answer questions, and submit the complete portfolio package.
Final Submission Package
1. MVP App
Working Streamlit app with scoring logic, rankings, and scouting shortlist outputs.
2. Product Brief
Problem statement, target users, MVP scope, ranking logic, and known limitations.
3. Pitch Deck
Problem, solution, interface, logic, business value, and final demo flow.
4. Sample Dataset
Tournament and match-wise CSV or spreadsheet used for demonstration.
5. Reflection Note
What students learned, what they would improve, and where the product can go next.
Evaluation Rubric
This program gives students something real.
Not just a certificate, but a visible product artifact, a demoable app, business thinking exposure, and a concrete introduction to how ideas become MVPs.