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LLM Building Blocks for Python Course

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talkpython/llm-building-blocks-for-python-course

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Dive intoLLM Building Blocks for Python, a concise 1.2-hour video course that equips you with everything you need to integrate large language models into your Python applications. You’ll learn to move beyond “text in → text out” by turning your prompts into structured data, orchestrating chat-style workflows, and building interactive prototypes. From rapid-fire notebook experiments to production-ready async pipelines and caching, this course gives you practical, code-first techniques for real-world LLM development.

What topics are covered

By the end of this course, you’ll be able to:

  • Set up and useMarimo for live, reactive notebook experiments
  • Install and configure thellm library and its plugins for multiple vendors
  • Craft prompts withPydantic schemas to enforce structured JSON outputs
  • Build and managechat conversations programmatically in Python
  • Orchestrateasync LLM calls and understand concurrency limits
  • Implementdisk caching to save tokens, speed up development, and cut costs
  • Measure classification accuracy andbenchmark LLM vs. scikit-learn pipelines
  • ConductA/B tests on prompts to iteratively refine model outputs
  • Explore higher-level tools likesmartfunk,Mirascope,Ollama, andInstructor
  • Design small “apps” inside Marimo to automate tasks such as YouTube transcript summarization

Who Should Take This Course?

  • Python developers curious about adding LLM features to scripts, tools, or web apps
  • Data scientists wanting to prototype NLP workflows without deep ML expertise
  • DevOps/automation engineers looking to integrate AI-driven tasks into pipelines
  • Tech leads and architects evaluating LLM toolchains for production use
  • Educators and researchers who need structured LLM interactions in their code

Take the course

VisitTalk Python Training to take the course for just $19 USD.

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