AI Essentials for Engineers

AI Essentials for Engineers

Learn how to integrate AI into engineering workflows with hands-on experience in LLMs, RAG, and AI agents. Covers foundational AI concepts, ethical guidelines, and practical tools like LangChain, OpenAI, Ollama, and LightRAG.

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Beginner
Artificial Intelligence
2 days

What you will learn in this course

This training provides engineers with a comprehensive introduction to AI, Generative AI, and Large Language Models (LLMs), focusing on real-world applications in software development and DevOps. Participants will gain hands-on experience with AI-powered tools and workflows, learning how to optimize AI models for automation, code generation, debugging, and infrastructure management. The course also emphasizes ethical considerations, compliance with the EU AI Act, and security best practices to ensure responsible AI implementation. Through interactive labs and guided exercises, participants will explore RAG techniques, AI-driven incident response, and LLM-based automation for monitoring, testing, and deployment. By the end of the training, attendees will have a solid understanding of AI’s role in engineering and the ability to integrate AI-powered solutions into their own workflows.

Agenda

Introduction to AI & Generative AI

Overview of the EU AI Act & Ethical Considerations

Understanding Large Language Models (LLMs)

Hands-on: LLM Deployment & Prompt Engineering

Retrieval-Augmented Generation (RAG) Basics

Hands-on: Building a RAG pipeline with LangChain

Advanced RAG: GraphRAG with LightRAG

Hands-on: AI-powered Knowledge Base

Ensuring AI Security & Compliance

Hands-on: Mitigating Prompt Injection Attacks

AI Agents & Autonomous Workflows

Hands-on: AI Agents for Incident Response

audience

This course is designed for

  • Software engineers
  • DevOps professionals
  • AI/ML practitioners

prerequisites

To get most out of this course, you should have:

  • Basic programming knowledge (Python recommended)
  • Familiarity with cloud platforms and version control (Git)

style

Our trainers have years of experience and will deliver the right mix of:

  • Interactive lectures
  • Hands-on labs with guided exercises
  • Real-world use case discussions
  • Group activities and Q&A sessions

Technical requirements

We recommend the following equipment:

  • Installed VSCode
  • Pre-configured VM with AI tools (Ollama, LangChain, LightRAG)
  • Cloud access (AWS, Terraform setup optional)
  • Internet connection for API-based demos

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