Programme Parameters
Foundation
4 Weeks (40 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Sports Analytics: Introduction course is a free, beginner-friendly self-paced program designed to help learners understand how data is used to analyze sports performance, strategies, and outcomes. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Sports Analytics: Introduction course is a free, beginner-friendly self-paced program designed to help learners understand how data is used to analyze sports performance, strategies, and outcomes.
📋 Course Objectives
1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to Sports Analytics
What is Sports Analytics? • Role of Data in Sports Performance • Traditional vs Data-Driven Sports Analysis • Applications in Different Sports
Understanding Sports Data
Types of Sports Data: Player Stats and Match Data • Performance Metrics and Indicators • Data Collection in Sports • Importance of Accurate Data
Basic Analytics Techniques
Analyzing Player Performance • Team Strategy Analysis • Trend and Pattern Identification • Simple Data Interpretation
Applications of Sports Analytics
Player Selection and Scouting • Game Strategy and Decision-Making • Injury Prevention and Fitness Monitoring • Fan Engagement and Business Insights
Future Scope and Next Steps
AI in Sports Analytics • Technology in Modern Sports • Career Opportunities in Sports Analytics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Sports Analytics |
| Covered Tool / Platform | Performance Metrics |
| Covered Tool / Platform | Data Analysis |
| Covered Tool / Platform | Statistics |
| Covered Tool / Platform | Data Insights |
Frequently Asked Questions
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