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Building with AI

The practitioner track — how to actually build useful AI products. This is where our courses go deep.

Building with AI is one of the core areas in the AI University map of AI. Explore the diagram, then dive into each topic — every subtopic grows into its own deep-dive over time.

flowchart LR
  IDEA[/Use case/] --> PROMPT[Prompt] --> RAG[Add RAG] --> AGENT[Add tools / agent] --> EVAL[Evals] --> SHIP[[Ship]]

Key topics

  • Prompt engineering

    Reliable prompting patterns for real applications.

  • Building RAG systems

    Chunking, embeddings, retrieval, and grounding end to end.

  • Building agents

    Tools, memory, control loops, and evaluation for agentic apps.

  • Fine-tuning & evals

    When to fine-tune, and how to build evals you trust.

  • Shipping to production

    Cost, latency, safety, and deploying on the edge.

NLP & Large Language Models · AI Agents & Autonomy · Data & MLOps · Applications & Industry

Learn this properly

Want hands-on training in building with ai? Explore AI University courses and AI School camps for kids.