Generative AI To Research, Design, Write,Create Top Projects
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Generative AI To Research, Design, Write,Create Top Projects
$49.99
Description
-
2025 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI
★★★★★
$13.00 in stock
Udemy.com
as of January 6, 2026 10:26 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
CEO of AI Accelera and Aceleradora AI
Rating:4.48 (2229reviews)
22733students 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.
Price History
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