2024 Bootcamp: Generative AI + LLM App Development. | Udemy [Update 03/2024]
English | Size: 9.64 GB
Genre: eLearning[/center]

From zero to professional level: learn the keys to AI and build the most potential Generative AI applications.

What you'll learn
Keys to Artificial Intelligence and the new Generative AI.
LLM Apps with LangChain, CrewAI, LangGraph, LangServe and LangSmith.
How to create an LLM Application from scratch to professional level.
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.

This Online Bootcamp 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. You will also learn how to build Advanced RAG LLM Apps, Multimodal LLM Apps, AI Agents, Multi-Agent LLM Apps, and how to manage LLMOps.

By the end of this program, you will know how to do the following:

AI AND BUSINESS

Know the businesses that AI puts at risk of disappearing.

Know the new opportunities created by AI for businesses.

Design a plan to introduce AI into your company.

Select an appropriate pilot project to introduce AI into your company.

Form the first AI team in your company.

Prepare your company's AI strategy.

AI AND STARTUP

Identify 100 opportunities to create AI startups.

AI AND EMPLOYMENT

Know the professions that AI puts at risk of disappearing.

Know the new professions created by AI.

LLM APPLICATIONS, THE APPLICATIONS WITH THE GREATEST POTENTIAL OF GENERATIVE AI.

Know the main use cases of LLM Applications in businesses and startups.

RAG LLM Applications.

Multimodal LLM Applications.

AI Agents.

Multi-Agent LLM Applications.

CREATION OF PROFESSIONAL LLM APPLICATIONS.

You will learn the Architecture of an LLM Application.

You will learn how to learn programming languages like Python and Javascript.

You will learn to work with your computer's terminal.

You will learn to work with Jupyter notebooks.

You will learn to work with code editors like Visual Studio Code.

You will learn to work with virtual environments.

You will learn to work with hidden files to save credentials.

You will learn the RAG (Retrieval Augmented Generation) technique.

You will learn to use LangChain.

You will learn to use the LangChain Expression Language (LCEL).

You will learn LCEL in depth.

You will learn to use the new versions v010 and v020 of LangChain.

You will learn to use LlamaIndex.

You will learn to use the OpenAI API.

You will learn to use OpenAI's functions.

You will learn to use LangSmith.

You will learn to use LangServe.

You will learn to use templates of LangChain and LlamaIndex.

You will learn what AI Agents are and how to create them.

You will learn to create prototypes (demos) of LLM applications with LangChain and Streamlit.

You will learn to create full-stack CRUD applications with Nextjs, FastAPI, and Postgres.

You will learn to create professional full-stack LLM applications with LangChain, LlamaIndex, Nextjs, Tailwind CSS, FastAPI, Flask, and Postgres.

You will learn to use vector and traditional databases.

You will learn to deploy applications on Vercel and Render.

You will learn to use AWS S3 as a remote storage platform.

You will learn to use ChatGPT as a programming assistant.

You will learn to use GPT4-Vision.

You will learn to work with Github and Github Codespaces.

You will learn what LLMOps is and how to use it in your LLM Applications.

You will learn the principles of Responsible AI and how to use them in your LLM Applications.

You will learn how to build advanced RAG LLM Applications.

You will learn how to build the new Multimodal LLM Applications.

You will learn how to build the new AI Agents.

You will learn how to build the new Multi-Agent LLM Applications.

You will learn to use LangGraph.

You will learn to use CrewAI.

The Bootcamp consists of:

Almost 400 lessons divided into 56 sections.

More than 350 videos.

More than 260 attached presentations.

More than 150 practical notebooks.

35 practical code repositories on Github.

40 LLM applications of different difficulty levels: basic, intermediate, and advanced.

Material for more than 200 hours of study and practice for the student.

2 downloadable books valued at $50: "Keys to Artificial Intelligence" and "100 AI Startups that made more than $500,000 before the first year".

Topics included in this Bootcamp:

AI, Generative AI, AI Applications, LLM Applications, Multimodal LLM Applications, chatGPT, Llama2, GPT-4 Vision, Full-Stack Applications, LangChain, LangChain Expression Language (LCEL), LangChain v010, LangChain v020, LlamaIndex, OpenAI, OpenAI API, RAG, RAG Technique, Vector databases, Postgres, Pinecone, Chroma, DeepLake, Streamlit, Nextjs, Tailwind CSS, Vercel, FastAPI, Flask, Render, AWS S3, LangSmith, LangServe, LangChain Templates, LlamaIndex Templates, LLMOps, Responsible AI, LangGraph, CrewAI, Multi-Agent LLM Apps, AI Agents, Groq, Llama3, Mixtral.

Who this course is for:
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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