2024 Bootcamp: Generative AI + LLM App Development
2024 Bootcamp: Generative AI + LLM App Development
From zero to professional level: learn the keys to AI and build the most potential Generative AI applications.
Created by Julio Colomer | 21 hours on-demand video course
This 2024 Bootcamp: Generative AI + LLM App Development Online Courses is a compact and accelerated version of our 400-hour in-person master’s program.
It has two parts:
- In Part 1, you will learn the keys to Artificial Intelligence and the new Generative AI, as well as its potential to revolutionize businesses, startups, and employment.
- In Part 2, you will learn to build professional-level LLM Applications, the most potential applications of Generative AI.
Topics included in this Generative AI Bootcamp:
AI, Generative AI, AI Applications, LLM Applications, Full-Stack Applications, LangChain, LangChain Expression Language (LCEL), LangChain v010, LlamaIndex, OpenAI, OpenAI API, RAG, RAG Technique, Vector databases, Postgres, Pinecone, Chroma, DeepLake, Streamlit, Nextjs, Vercel, FastAPI, Render, AWS S3, LangSmith, LangServe, LangChain Templates, LlamaIndex Templates, LLMOps, Responsible AI.
What you’ll learn
- Keys to Artificial Intelligence and the new Generative AI.
- Keys to LLM Applications, the highest potential applications of Generative AI.
- How to create an LLM Application from scratch to professional level.
- Opportunities and threats of AI for businesses, startups, and jobs.
- Professional opportunities opened by Artificial Intelligence.
- Steps to become an Artificial Intelligence Engineer.
- How to introduce Artificial Intelligence into your business.
- 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.
- 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.
- LLMOps.
- How to apply the principles of Responsible AI.
- Daily tools of the AI Engineer: Jupyter Notebooks, Python, Terminal, Github, Codespaces, etc.
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The Generative AI Bootcamp consists of:
- 238 lessons divided into 36 sections.
- More than 200 videos.
- More than 150 attached presentations.
- More than 70 practical notebooks.
- 17 practical code repositories on Github.
- 25 LLM applications of different difficulty levels: basic, intermediate, and advanced.
- Material for more than 100 hours of study and practice for the student.
