Generative AI and LLM Applications topics
10 short topics in Generative AI and LLM Applications. Each one is a single focused exercise with a clear piece of evidence at the end.
10 topics, one exercise each.
Work through them in order, or jump to the one you need.
These are draft topic outlines (draft; instructor review pending). Full lessons follow after review; ask Ajay if you need a topic sooner.
- 01
Tokens and tokenization
Implement a focused example of Tokens and tokenization within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 02
Language model inference
Implement a focused example of Language model inference within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 03
Prompt context and instructions
Implement a focused example of Prompt context and instructions within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 04
Structured model outputs
Implement a focused example of Structured model outputs within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 05
Streaming model responses
Implement a focused example of Streaming model responses within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 06
Multimodal inputs and outputs
Implement a focused example of Multimodal inputs and outputs within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 07
Tool-calling interfaces
Implement a focused example of Tool-calling interfaces within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 08
Context-window management
Implement a focused example of Context-window management within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 09
Hallucinations and uncertainty
Implement a focused example of Hallucinations and uncertainty within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course → - 10
LLM application cost and latency
Implement a focused example of LLM application cost and latency within a small part of Streaming AI feature with output validation; demonstrate a normal and an edge or failure case.
Open micro-course →
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