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Agentic AI: Building Agents

40 hoursIntermediate7 modules

1 of 7 modules with a published syllabus

0 of 7 modules recorded

Syllabus

Works through the operational definition of an agent — an LLM plus tools plus a loop —, the practical distinction between a chatbot and an agent, and then the three modules that make up the engineering of the subject: function calling and tool use, memory and state, and the orchestration frameworks. The AI APIs and prompt engineering module comes in as shared groundwork, and agent security (prompt injection, sandboxing) closes it, because an agent holding tools is an attack surface.

Modules of this programme

The same objects as the full curriculum. A module opened from any programme that contains it is the same module, with the same syllabus and the same status.

  • AG-101Syllabus published

    What agents are: LLM + tools + loop

    Detailed syllabus not written yet

  • AG-102Syllabus published

    Chatbots vs. agents (hands-on with APIs)

    Detailed syllabus not written yet

  • CORE-205Syllabus published

    AI APIs and prompt engineering

    Content
    OpenAI/Anthropic/OSS, function calling, cost
    Hands-on
    A CLI app that calls an LLM through an API

    estimated price0 of 1 module published

  • AG-201Syllabus published

    Function calling and tool use

    Detailed syllabus not written yet

  • AG-202Syllabus published

    Agent memory and state

    Detailed syllabus not written yet

  • AG-203Syllabus published

    Frameworks (LangGraph, CrewAI, agent SDKs)

    Detailed syllabus not written yet

  • AG-304Syllabus published

    Agent security (prompt injection, sandboxing)

    Detailed syllabus not written yet

Not everything fits into 40 hours. State of the art, distributed training, interpretability, edge deployment and the five integrative projects exist only inside the complete tracks: Tracks