The course is intended for participants who already have a basic understanding of algorithms and want to explore the use of Large Language Models (LLMs) and their APIs.
Familiarity with one of the programming languages (Python, TypeScript, JavaScript, C/C++, etc.) is recommended but not required.
During the course, participants will learn:
how to use LLMs and their APIs effectively,
how to automate processes using AI agents,
the concept of Retrieval-Augmented Generation (RAG) and the use of vector databases.
In the practical part, we will develop a simple multimodal chatbot and a personal AI assistant, using the Python programming language.
Content
Use of Large Language Models (LLMs) and local models with Ollama
Working with LLM APIs
Introduction to AI agents and their capabilities
Development of a multimodal chatbot with a user interface in Gradio
Learning the basics of RAG (Retrieval-Augmented Generation) and vector databases (ChromaDB)
Creating a personal AI assistant
Using the Python programming language in the development of LLM-based solutions
Recommended prior knowledge
Znanje enega izmed programskih jezikov (Python, TypeScript, JavaScript, C/C++ ipd.) je dobrodošlo, a ni obvezno.
Learning objectives
Understand the operation and use of Large Language Models (LLMs) and their APIs
Gain practical experience with local LLMs (e.g., Ollama)
Learn how to automate processes using AI agents
Develop a multimodal chatbot with a user interface (Gradio)
Understand the concept of Retrieval-Augmented Generation (RAG) and the use of vector databases
Create a personal AI assistant in Python
Target group
For anyone who wants to get acquainted with the use of LLMs, basic use of LLM APIs, and the fundamentals of AI agents.