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AI Engineer

Become an AI Engineer: LLMs, prompt engineering, RAG, vector databases, embeddings, AI agents, MCP and model integration in production.

7 moduli 25 argomenti ~19h totali

Programma del Corso

Transformers, tokenization and how language models work.

  • 1

    Transformer Architecture

    Attention, self-attention, encoder-decoder, positional encoding.

    1h
  • 2

    Tokenization

    BPE, SentencePiece, token counting, context window.

    40 min
  • 3

    Models Overview

    GPT-4o, Claude, Gemini, Llama 3, Mistral: comparison.

    35 min
  • 4

    LLM API Calls

    OpenAI SDK, temperature, top-p, streaming, function calling.

    45 min

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AI Engineering