| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Basic / Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | A/B Testing Experimentation Data Analysis Conversion Metrics User Behavior Analysis |
About the Data Science for Supply Chain: Basics Course
The Introduction to A/B Testing course is a free, beginner-friendly self-paced program designed to help learners understand how experiments are used to compare different versions of a product, webpage, campaign, or strategy.
The course introduces key concepts such as control groups, test groups, user behavior analysis, and result interpretation. Learners will explore how A/B testing helps organizations make data-driven decisions in marketing, product development, websites, and business optimization.
Program Highlights
• Free beginner-level A/B testing course
• Online self-paced learning format
• Simple explanation of experimentation and testing concepts
• Covers test design, comparison, and result interpretation basics
• Real-world examples from marketing and product analytics
• Suitable for students and first-time learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to A/B Testing
- What is A/B Testing?
- Importance of Experimentation in Decision-Making
- Control Group vs Test Group
- Applications of A/B Testing
Module 2: Understanding Test Design
- Creating Variations for Testing
- Selecting Metrics and Goals
- Understanding User Behavior Data
- Importance of Fair and Reliable Testing
Module 3: Running and Analyzing Tests
- Collecting and Comparing Results
- Understanding Conversion and Engagement Metrics
- Basic Statistical Thinking in Testing
- Interpreting Test Outcomes
Module 4: Applications of A/B Testing
- Website and App Optimization
- Marketing Campaign Testing
- Product and User Experience Improvements
- Business Decision-Making Through Experiments
Module 5: Future Scope and Next Steps
- A/B Testing in Data Science and Analytics
- Role of AI in Experimentation
- Career Opportunities in Analytics and Product Testing
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
A/B Testing Experimentation Data Analysis Conversion Metrics User Behavior Analysis
Real-World Applications
- Testing website layouts and user interfaces
- Comparing marketing campaign performance
- Improving product and app experiences
- Understanding customer preferences using experiments
- Supporting data-driven business decisions
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, marketers, entrepreneurs, product learners, and professionals interested in experimentation and analytics.
- It is also useful for learners from business, marketing, management, data analytics, product development, and non-technical backgrounds.
Certification
