NPTEL
FreeMaster Complete AI Engineering Concepts in 12 Hours!
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This long video is organized as a numbered sequence of sections, from an introduction to building AI applications on foundation models, through evaluation and prompt engineering, to RAG, agents, fine-tuning, dataset engineering and inference optimization. The final section covers architecture and user feedback.
Learners who want one continuous pass through the full AI engineering stack will value the sequence. Because the running time is long, it works well split across several sessions, with the timestamps as bookmarks.
Learn the concepts needed to master the AI Engineering roadmap, Adapted from the popular book on AI Engineering by Chip Huyen, learn the entire stack of AI Engineering taught in 12 hours. Your one shot video to learn AI Engineering concepts. It took me months to understand AI Engineering, and I distill it down in 12 hours for learners. Dear all, notes will be updated regularly, in the GitHub link of channel description, and comment pinned below.
Timeline(Notes in Pinned Comments)
1. Introduction to Building AI Applications with Foundation Models(0:00 - 36:13)
2. Understanding Foundation Models.( 36:13 - 1:59:55)
3. Evaluation Methodology.(1:59:55 - 3:06:48)
4. Evaluate AI Systems.(3:06:48 - 3:56:14)
5. Prompt Engineering.(3:56:14 - 4:43:04)
6. RAG and Agents.(4:43:04 - 6:03:07)
7. Finetuning.(6:03:07 - 7:34:52)
8. Dataset Engineering.(7:34:52 - 8:53:26)
9. Inference Optimization.(8:53:26 - 11:05:53)
10. AI Engineering Architecture and User Feedback.(11:05:53 - End)
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