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Generative AI Basics for Beginners (Open AI, LLM, Models)

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Last updated on November 3, 2026 12:39 am

2025 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI

★★★★★
$3,129.00
$509.00
 in stock
as of November 3, 2026 12:39 am

From zero to professional level: learn the keys to Generative AI, LLM Apps, AI Agents, and Cursor AI.

Created by: Julio Colomer
CEO of AI Accelera and Aceleradora AI
Rating:4.48 (2229reviews)     22707students enrolled

What Will I Learn?

  • Keys to AI, Generative AI, LLM Apps, and new AI Coding Assistants like Cursor AI.
  • LLM Apps with LangChain, CrewAI, LangGraph, LangServe and LangSmith.
  • How to build apps without coding using Cursor AI and AI Coding Assistants.
  • How to build the new Multimodal and Multi-Agent LLM Applications.
  • Opportunities and threats of AI for businesses, startups, and jobs.
  • RAG Applications in Depth: Full Stack RAG Apps and Advanced Techniques.
  • How to manage LLMOps: Observability, Evaluation, Testing, Etc.
  • Professional opportunities opened by Artificial Intelligence.
  • Steps to become an Artificial Intelligence Engineer.
  • How to introduce Artificial Intelligence into your business.
  • Keys to LLM Applications, the highest potential applications of Generative AI.
  • Architecture of professional LLM Applications.
  • The RAG Technique (Retrieval Augmented Generation).
  • Artificial Intelligence Agents.
  • Basic and advanced LangChain, LangChain LCEL, and LangChain v010. LangSmith, LangServe, LangChain Templates.
  • LCEL (LangChain Expression Language) in depth.
  • Basic and advanced LlamaIndex. LlamaIndex Templates.
  • ChatGPT, OpenAI, OpenAI functions, and the OpenAI API.
  • Large Language Models (LLM): ChatGPT, Llama2, Mistral, Falcon, etc.
  • Vector databases: Postgres, Pinecone, Chroma, FAISS, DeepLake, etc.
  • Full-Stack Applications: Nextjs and FastAPI.
  • Professional deployment: Vercel and Render.
  • Provisional deployment: Streamlit.
  • Cloud hosting: AWS S3.
  • How to apply the principles of Responsible AI.
  • Daily tools of the AI Engineer: Jupyter Notebooks, Python, Terminal, Github, Codespaces, etc.

Requirements

  • No previous technical knowledge is required.
  • Students with some prior knowledge will improve their professional preparation.

Target audience

  • Students and professionals with and without previous experience.
  • Students without prior knowledge interested in taking advantage of the professional opportunities opened by the field of Artificial Intelligence.
  • Executives interested in introducing Artificial Intelligence into their company.
  • Machine Learning, Deep Learning, and Data Science professionals interested in expanding their professional opportunities in the area of Generative AI and LLM Applications.
  • Software application developers interested in expanding their professional opportunities by learning to develop Generative Artificial Intelligence and LLM Applications.

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