Level Up Your Python Gen AI Skills: Nine-Part YouTube Stream Series
Pamela Fox presents a comprehensive nine-part YouTube series teaching developers how to harness generative AI in Python, including Azure AI services, LLMs, vision AI, RAG, safety, agents, and real-world coding techniques.
Level Up Your Python Gen AI Skills: Nine-Part YouTube Stream Series
Presented by Pamela Fox
Are you interested in implementing generative AI in your Python applications? This free live stream series delivers hands-on learning across nine in-depth sessions, with support for both English and Spanish speakers. You’ll gain practical AI development skills with Python, plus the opportunity for live Q&A via weekly office hours on Discord.
Series Overview
- Large Language Models (LLMs): Learn the fundamentals of LLMs like those behind ChatGPT and GitHub Copilot. Practice prompt engineering, improve results with few-shot examples, and build a full-stack LLM-powered app. Python code examples rely on the OpenAI SDK and LangChain.
- Vector Embeddings: Understand how text and images are encoded as vectors. Experiment with vector search, distance metrics, and quantization using OpenAI’s embedding models and Python libraries.
- Retrieval Augmented Generation (RAG): Implement RAG pipelines to deliver grounded, domain-specific answers. Work through Python-based RAG flows and build a full-stack RAG app powered by Azure AI Search.
- Vision Models: Interact with multi-modal LLMs like GPT-4o. Develop Python solutions for image captioning, classification, and chat-on-images, building a multimodal search engine.
- Structured Outputs: Guide LLMs to emit structured, schema-compliant responses using @dataclass and Pydantic. Apply these to real use cases including entity extraction, workflow orchestration, and classification.
- AI Safety and Evaluations: Apply safety standards and evaluate output quality with Azure AI tools. Configure Azure AI Content Safety, handle exceptions in Python, and use the Azure AI Evaluation SDK for robust, ethical results.
- Tool and Function Calling: Aggregate tool integrations for LLMs and improve user experiences.
- AI Agents: Build advanced agents with frameworks like Langgraph, Semantic Kernel, Autogen, and Pydantic AI. Practice hand-offs, supervisor models, and custom workflows.
- Model Context Protocol (MCP): Explore this open protocol for extending AI agents and bots. Learn to develop MCP servers using FastMCP SDK and integrate with chatbots such as GitHub Copilot and agent frameworks.
Registration
Session Dates (October 2025)
- Large Language Models: 7 October
- Vector embeddings: 8 October
- Retrieval Augmented Generation: 9 October
- Vision models: 14 October
- Structured outputs: 15 October
- Quality and safety: 16 October
- Tool calling: 21 October
- AI agents: 22 October
- Model Context Protocol: 23 October
Each session offers hands-on demonstrations, practical coding, and integration of Microsoft AI offerings for real-world solutions.
Who Should Attend?
- Python developers
- AI/ML engineers interested in Microsoft AI tools
- Full stack engineers exploring advanced AI integrations
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Author: Pamela Fox
Published: October 6, 2025
This post appeared first on “Microsoft Tech Community”. Read the entire article here