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IT & Tech

Generative AI CodingBootcamp.

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NodCoding logotyp
NodCoding
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A 10-week, full-time coding bootcamp in Stockholm focused on generative AI engineering. Students learn Python and software development fundamentals, then build AI agents, retrieval-augmented generation (RAG) systems and tool integrations using LangChain, LangGraph and the Model Context Protocol (MCP). Cohorts are capped at 12 students, with the same job-focused, project-based approach as Nod's other bootcamps.

Längd: 10 veckor
Format: På plats
Ort: Stockholm
Språk: Engelska
Nivå: Nybörjare

Omfattning: Full-time, Mon-Fri 09:00-17:00

Begär info

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Om kursen.

Has successfully completed the 10 week coding bootcamp consisting of at least 350 hours of hands-on coding.

Kursinnehåll

Vad du lär dig.

  • Write Python programs as a foundation for AI engineering
  • Build AI agents that make dynamic decisions and interact with their environment
  • Implement retrieval-augmented generation (RAG) using vector storage
  • Integrate external tools such as web scraping, voice, image and calendar/email APIs
  • Connect AI tools to data sources securely using MCP (Model Context Protocol)
  • Use LangChain and LangGraph to build and orchestrate AI applications
  • Pass a technical interview for an entry-level AI/software engineering role
Upplägg

Så är kursen upplagd.

  1. Python Programming

    Foundational programming skills for software and AI development.

  2. Software Development

    Entry-level developer practices and tooling.

  3. AI Agents

    Building agentic systems that reason and act dynamically.

  4. RAG (Retrieval-Augmented Generation)

    Enhancing model outputs with external data and vector search.

  5. Tool Integration

    Connecting AI apps to web scraping, voice, image and calendar/email tools.

  6. MCP (Model Context Protocol)

    Securely connecting AI tools to external data sources.

Målgrupp

Vem passar kursen?

Beginners through those with some programming background who want to become AI/GenAI engineers; no prior coding experience is required, though pre-course preparation is expected.

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