GPT and Open Source LLM App Dev

Course Description

The fast pace of development in LLMs and related technologies made it possible to use them even in enterprise grade applications. There are already a few areas where a new generation of LLM-based applications totally redefined applications' capabilities and users' expectations while AI technologies are going to radically change all kinds of other software areas as well.

That's why software developers as well as other IT professionals and technical managers need to understand these technologies, especially agentic AI, and need to have practical skills to use them in their daily work.

Main topics:

• Introduction to LLM based applications
• Main parts, working and training of LLMs
• Using closed- and open-source LLMs via APIs
• Creating LLM chains with LangChain
• Fast Web Interface Prototyping for LLMs
• Prompt engineering for chatbots and agents
• Retrieval Augmented Generation (RAG)
• LLM-based Agentic Systems
• Workflows, Deep Agents, Multi-agent Systems and Agentic Frameworks (optional)
• Tracing and Evaluating LLM-based apps

With the help of these building blocks a team of engineers is capable of developing cutting edge applications like customer service bots, knowledge base managers and research assistants.

Besides learning about LLM concepts, students will also do extensive lab exercises using the Python APIs of popular closed-source OpenAI GPT, Google Gemini, Anthropic Claude as well as open-source Meta's Llama and Mistral models LLMs to see how these concepts work in practice. During the exercises they use LangChain products such as LangChain, LangGraph and LangSmith, to implement LLM concepts in real world LLM applications.

Target Audience

Software developers, testers, devops as well as other IT professionals and technical managers with technical backgrounds who want to understand the basic concepts and technologies behind Large Language Models (LLMs) and want to obtain practical skills in LLM application development with the Python APIs of popular closed- and open-source LLMs and open-source frameworks.

Prerequisites

Basic understanding of AI concepts, basic Python programming skills, user experience with ChatGPT or similar chatbots.