Generative AI
Generative AI, LLMs & AI & ML Engineering Fundamentals
Understand how LLMs actually work — transformers, tokenization, training and optimization — and design enterprise AI strategy.
Course Topics
This is a snapshot of what's covered. Contact us for the complete module-by-module curriculum, batch schedule, and pricing.
Skills covered
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- Live + recorded sessions with lifetime access
- Hands-on labs & real projects
- Certificate of completion
- Mobile learning & downloadable resources
- Instructor Q&A & discussion forums
About this course
A deep, engineering-grade foundation in Generative AI: neural networks, transformer architecture and attention, tokenization and embeddings, why hallucinations occur, model training and alignment, and optimization techniques like quantization and Mixture of Experts — plus Responsible AI, governance and enterprise AI strategy design.
What you'll learn
- Explain transformer architecture and attention mechanisms
- Understand tokenization, embeddings & context windows
- Explain how LLMs generate text and why hallucinations occur
- Understand pre-training, instruction tuning & alignment
- Apply Responsible AI, safety & governance principles
- Design an enterprise AI strategy
Program Roadmap
1
AI, ML, Deep Learning & LLM Foundations
2
Transformers & Attention
3
Model Training & Alignment
4
Model Optimization
5
Responsible AI & Governance
6
Enterprise AI Strategy Capstone
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