Programme Parameters
Graduate / Intermediate
4 Weeks (40 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Generative AI Certificate Course is a structured, credential-bearing path through the technology reshaping work and creativity. You learn how generative AI works — language and image models — how to use them effectively through prompting, and how to build simple generative applications, alongside the ethics and limits of the technology. It culminates in a credential recognising your generative-AI competency. You finish certified and able to understand, use and build with generative AI. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This certificate course provides a structured foundation in generative AI — how generative models and LLMs work, how to use and build with them, culminating in a credential.
📋 Course Objectives
1. Explain how generative models and LLMs work.
2. Use generative-AI tools effectively.
3. Apply prompting and adaptation.
4. Build a simple generative application.
5. Address ethics and limits.
👥 Who Should Enroll?
• Professionals adopting generative AI
• Developers entering the field
• Students seeking a GenAI credential
• Anyone building GenAI skills
🚀 Key Learning Outcomes
• A certified generative-AI foundation.
• Practical build-and-use skills.
• A recognised credential.
• 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
AI Fundamentals, Mathematics, and Generative Ai Certificate Foundations
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Data Engineering, Preprocessing, and Feature Pipelines
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Model Architecture, Algorithm Design, and Generative Ai Certificate Methods
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Training, Hyperparameter Optimization, and Evaluation
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Deployment, MLOps, and Production Workflows
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Ethics, Bias Mitigation, and Responsible AI Practices
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Industry Integration, Business Applications, and Case Studies
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Advanced Research, Emerging Trends, and Generative Ai Certificate Innovations
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Capstone: End-to-End Generative Ai Certificate AI Solution
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Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Certificate |
| Covered Tool / Platform | Course |
| Covered Tool / Platform | Generative |
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