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AI Fundamentals Guide

56

Lecciones

8

Módulos

🎓

Acceso por bootcamp

Lo que aprenderás

Explain AI, ML, Deep Learning, and Generative AI with technical clarity
Understand how neural networks work conceptually (layers, activation, backpropagation)
Explain the Transformer architecture and why it revolutionized AI
Understand how LLMs work: tokenization, embeddings, context window, temperature
Compare major LLMs (GPT-4, Claude, Llama, Mistral) across key dimensions
Navigate the AI API ecosystem: providers, pricing, open-source vs proprietary, local vs cloud
Differentiate AI Engineering from ML Engineering and Data Science
Design high-level AI system architectures (chatbots, RAG, Q&A systems)

¿Para quién es?

  • Developers who want to become AI Engineers and need a solid conceptual foundation before building
  • Software engineers adding AI features to their products who need to understand how LLMs and APIs work
  • Tech professionals transitioning into AI roles who need to understand the modern AI stack without a math-heavy approach
  • Bootcamp students preparing for the AI Engineering Bootcamp who want a strong theoretical base
  • Anyone technically curious who wants to understand Transformers, LLMs, and the AI ecosystem at a level deeper than surface-level hype

Requisitos

  • Curiosity about AI and technology
  • Ability to read technical documentation in English
  • Basic understanding of programming (what code is, what a function does)
  • No advanced math required (no linear algebra, no calculus)
  • No Python or Machine Learning experience needed

Contenido del curso

1Módulo 1: ¿Qué es AI Realmente?6 lecciones
2Módulo 2: Machine Learning Fundamentals7 lecciones
3Módulo 3: Neural Networks & Deep Learning8 lecciones
4Módulo 4: Transformers - La Revolución del AI Moderno8 lecciones
5Módulo 5: LLMs (Large Language Models) - GPT, Claude y Más8 lecciones
6Módulo 6: El Ecosistema de AI APIs7 lecciones
7Módulo 7: AI Engineering - El Nuevo Rol6 lecciones
8Módulo 8: Tu Primer Diseño de Sistema AI6 lecciones
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