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AI Engineering

2 days · Interactive workshop

You gain the necessary know-how to choose LLMs, run and manage them locally, connect your company’s documents and data to the model through RAG, and embed AI into your existing applications. You put this into practice by building an incident-management system step by step throughout the workshop.

Who it is for

For developers and technical leads who want to use AI to improve their company’s processes and create business value.

What you leave with

  • Set up and run a model on your local machine and connect it to an application.
  • Build a RAG system that provides access to internal documents and databases.
  • Integrate the model and RAG into a fully agentic application, with humans in control.

Syllabus

Model

LLM Basics and Local Models

  • LLM fundamentals: tokens, context, agents, capabilities and limitations
  • Overview of models: hosted and local
  • Local inference engines: llama.cpp and vLLM
  • Hardware requirements and costs
  • Setting up and running a local model yourself
  • Connecting your application to a local or hosted model

Context

Company Knowledge, Internal Documents and Data

  • Providing instructions and context through skills
  • Connecting tools and information sources through MCP servers
  • Preparing and chunking company documents
  • Embedding models and creating embeddings for documents and queries
  • Vector stores, semantic search and hybrid retrieval
  • Reranking retrieved results
  • Providing retrieved information and source references to the model
  • Authentication and authorization for company documents and data
  • Evaluating retrieval quality and generated answers
  • Exposing company knowledge through MCP tools

Agents

Company Applications Powered by AI

  • Overview of agentic frameworks: Mastra, Microsoft Agent Framework and LangGraph
  • Introduction to Google ADK
  • Agents and tool calling
  • Workflows
  • Deterministic tools
  • Classification and decision models, such as Jev
  • Connecting your UI to agents with AG-UI
  • Human approval and control
  • Evaluating agent behaviour and handling uncertainty

Starting knowledge: Programming experience and familiarity with APIs. Prior machine-learning experience is not required.

Dates and pricing

Tell us about your team, current experience, and what you want to achieve. We will discuss the scope, format, duration, and pricing with you.

You can book this workshop independently. For goals spanning several topics, explore our custom programmes.

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