LangChain Python topics
12 short topics in Generative AI and LLM Applications. Each one is a single focused exercise with a clear piece of evidence at the end.
12 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
Model and provider interfaces
Demonstrate model and provider interfaces in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 02
Prompt and context composition
Demonstrate prompt and context composition in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 03
Message and conversation representation
Demonstrate message and conversation representation in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 04
Structured response contracts
Demonstrate structured response contracts in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 05
Response streaming
Demonstrate response streaming in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 06
Tool-calling integration
Demonstrate tool-calling integration in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 07
Retrieval integration boundaries
Demonstrate retrieval integration boundaries in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 08
Application state and memory strategy
Demonstrate application state and memory strategy in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 09
Failure retry and fallback policy
Demonstrate failure retry and fallback policy in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 10
Token cost and latency measurement
Demonstrate token cost and latency measurement in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 11
Evaluation fixture design
Demonstrate evaluation fixture design in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
Open micro-course → - 12
Framework integration and upgrade testing
Demonstrate framework integration and upgrade testing in a focused LangChain Python example; verify normal behavior and one edge or failure case. Keep the exercise bounded and record the behavior supported by the chosen version.
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Learn the same ideas beyond LangChain Python.
These courses share topics with this one, so you can compare how each language or tool handles the same concept.
More in LLM agent and retrieval frameworks.
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