Practical development and implementation of Large Language Models (LLM)/AI workflows
The training lasts 2 days and includes the opportunity to learn how to build intelligent AI workflows and assistants using large language models (LLM), as well as tools such as n8n and LangFlow.
There will also be an opportunity to learn more about RAG architecture, agent management (MCP, A2A), prompt engineering and the use of local models, as well as to work practically, for example, by creating bots and testing different models. The learning process uses examples that will then be applied in a real work environment.
Andrejs Adamovičs
Since 2011, Andrejs has been sharing his deep knowledge by leading his DevOps MasterClass (eXtreme Automation) course, which he has taught more than 200 times in various European locations, including Austria, Sweden, Denmark, Great Britain, Romania, Estonia and Latvia. His teaching courses include many practical exercises and real-life examples, always aiming to keep students interested in learning more.
In addition to his professional activities, Andrejs is a frequent speaker at international conferences and local community events. Andrej's versatile approach to technology and education makes him a valuable mentor and leader in the IT community.
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Course Target
Developing a comprehensive understanding and practical skills in:
- integrating large language models into various processes;
- building AI workflows;
- AI agents;
- building controllable and repeatable AI solutions.
Au
- Developers;
- DevOps and infrastructure specialists;
- Automation engineers;
- Data engineers;
- Solution architects;
- Anyone who wants to use AI tools and solutions in various projects and work processes.
At Course Completion you will be able to
- Understand the structure of AI workflows, LLM and agent applications.
- Apply tools such as n8n, LangFlow and RAG models in practical projects.
- Analyze and evaluate the cost, performance and usability of LLM solutions.
- Create a practical AI workflow or assistant.
Prerequisites
A general understanding of IT systems and an interest in automation and AI is desirable.
Training materials
Training materials and practical examples are prepared by BDA.
Certification exam
Not intended.
Course Outline
- Overview of the AI tools ecosystem: LMM, vector databases, orchestration.
- Practical application of n8n and LangFlow tools for AI flows.
- Prompt design and the structure of test questions.
- Embedding un Retrieval-Augmented Generation (RAG).
- Agent control models: MCP, A2A.
- Comparison of LLM (OpenAI, Claude, Mistral, LLaMA etc).
- Local models and their deployment (price vs performance).
If you want to get more information about this course, please contact us by phone +371 67505091 or send an e-mail at mrn@bda.lv.
