The course is intended for participants with basic knowledge of Python who want to expand their skills in the field of artificial intelligence. You will learn how large language models (LLMs) work and gain the ability to build practical AI solutions. The focus will be on working with LLM APIs and prompt engineering, using embeddings and RAG approaches, task automation with agents, and MCP servers. By the end of the course, you will have designed and developed your own AI application in Python.
Content
- Introduction to LLMs & the Python AI ecosystem
- Working with LLM APIs
- Prompt engineering
- Embeddings & RAG (Retrieval-Augmented Generation)
- Task automation with agents
- MCP servers (Model Context Protocol) in practice
- Building a practical AI application
Recommended prior knowledge
Participation in a basic Python course or knowledge of Python fundamentals.
Learning objectives
- Understand how large language models (LLMs) and modern AI approaches work.
- Master key tools and techniques: LLM APIs, prompt engineering, embeddings & RAG, agents, MCP servers.
- Design and develop your own practical AI application in Python.
Target group
- Anyone who wants to expand their knowledge in the field of artificial intelligence (AI).
- Developers, analysts, and professionals who are interested in using LLMs and modern AI approaches in practice.
2024-04-02 16:15:00
2025-12-23 10:41:00