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 Marketing Analytics: Introduction course is a free, beginner-friendly self-paced program designed to help learners understand how data is used to analyze marketing performance and improve business strategies. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Marketing Analytics: Introduction course is a free, beginner-friendly self-paced program designed to help learners understand how data is used to analyze marketing performance and improve business strategies.
📋 Course Objectives
1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 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 Marketing Analytics
What is Marketing Analytics? • Role of Data in Marketing • Traditional vs Data-Driven Marketing • Applications in Business and Digital Platforms
Understanding Marketing Data
Types of Marketing Data: Customer, Campaign, and Sales • Key Metrics: CTR, Conversion Rate, and Engagement • Customer Behavior and Insights • Importance of Data Quality
Basic Analytics Techniques
Analyzing Campaign Performance • Understanding Trends and Patterns • Introduction to Customer Segmentation • Simple Data Interpretation
Applications of Marketing Analytics
Digital Marketing and Social Media Analysis • Customer Targeting and Personalization • Campaign Optimization • Business Decision-Making
Future Scope and Next Steps
AI in Marketing Analytics • Career Opportunities in Marketing and Analytics • Learning Path for Digital Marketing and Data Analytics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Marketing Analytics |
| Covered Tool / Platform | Customer Insights |
| Covered Tool / Platform | Performance Metrics |
| Covered Tool / Platform | Data Analysis |
| Covered Tool / Platform | Campaign Tracking |
Frequently Asked Questions
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