A Deep Dive Into The Future Tech Of Chatgpt And Llms

From Zero to AI Hero: Dive Deep into ChatGPT, Large Language Models, LangChain, Pinecone, Flowise, Open-Source LLMs…

What you'll learn

Introduction to Large Language Models

Fundamentals of Generative AI and ChatGPT

Prompt Engineering for effective use of ChatGPT and LLMs

Language Modeling Tools (LLM) and NLP

Hugging Face: The GitHub of language models.

Giving Superpowers to LLMs with LangChain

Train ChatGPT with a customized knowledge base

Langchain and Agents: Giving new capabilities to LLMs

Working with Open-source models: ChatGPT4All

Requirements

ChatGPT Fundamentals

Description

Unlock the Future of Large Language Models and ChatGPT:  Dive deep into the next-generation tech that's revolutionizing how we interact, write, and think. This immersive course offers an unparalleled insight into Large Language Models (LLMs), the underlying tech behind ChatGPT, and a landscape of open-source models. Why This Course?1. **Comprehensive Curriculum:** From the basics of Udemy, foundational concepts of LLMs, to advanced practical labs on GPT4ALL and LangChain - we've covered it all.2. **Hands-On Experience:** Engage in hands-on labs, learning how to integrate tools, manage inputs, and unlock the potential of LLMs.3. **Cutting Edge Content:** Understand the mechanics behind ChatGPT's evolution, dive into Generative AI, and discover the power of Prompt Engineering.4. **Industry Expertise:** Harness the capabilities of Hugging Face, hailed as the 'GitHub of language models', and explore groundbreaking tools for working with LLMs and NLPs.5. **Application Development:** Master no-code application development with Flowise, opening new doors to AI-powered solutions. Who's This For?- AI enthusiasts eager to learn about the next big thing.- Developers wanting to incorporate LLMs into their tools.- Entrepreneurs looking to leverage AI for innovative solutions.- Students, educators, and researchers in AI and NLP fields. Course Highlights:- Get acquainted with Udemy, ensuring you harness the full potential of this platform.- Understand Large Language Models, from their inception to their diverse types.- Dive into the world of Generative AI - exploring models based on Transformers, Variational Auto Encoders, and more.- Get a behind-the-scenes look at OpenAI, the genius behind ChatGPT.- Understand and implement Prompt Engineering techniques for better LLM results.- Explore tools like OpenAI API, Hugging Face, and LangChain in detail.- Navigate the open-source world of LLMs and the benefits they bring.- Practical Labs: Experience hands-on training with tools, integration, and application development.- Special focus on application development with ChatGPT without code using Flowise. By the end of this course, you'll be well-equipped with the knowledge and practical skills to navigate the rapidly evolving world of ChatGPT and LLMs. Whether you're a curious individual, a budding developer, or a forward-thinking entrepreneur, this course holds the keys to the future of communication.Don't wait. Enroll now and be at the forefront of the AI revolution!

Overview

Section 1: Introduction to the Udemy platform

Lecture 1 Introduction to the Udemy platform

Section 2: Sust_Introduction to Large Language Models

Lecture 2 Introduction to Large Language Models

Lecture 3 What are Large Language Models

Lecture 4 Types of Language Models

Section 3: Fundamentals of Generative AI

Lecture 5 Introduction to Generative AI and its applications ChatGPT, DALLE, MidJourney

Lecture 6 Modelos discriminativos vs modelos generativos

Lecture 7 Redes Generativas Adversariales (GAN)

Lecture 8 Models based on Transformers

Lecture 9 Variational Auto Encoders and latent space

Lecture 10 Challenges of Generative AI

Section 4: Fundamentos de ChatGPT

Lecture 11 OpenAI: the company behind the ChatGPT algorithm

Lecture 12 Laboratorio: Primeros pasos con ChatGPT

Lecture 13 Limitations of ChatGPT

Section 5: ChatGPT4

Lecture 14 GPT4 The evolution of ChatGPT

Section 6: Prompt Engineering for effective use of ChatGPT and LLMs

Lecture 15 What is Prompt Engineering

Lecture 16 How to get better results with LLMs

Lecture 17 Prompt Engineering Techniques for ChatGPT

Section 7: Language Modeling Tools (LLM) and NLP

Lecture 18 Tools for working with LLMs and NLPs

Lecture 19 Open AI API

Lecture 20 Hands-on Lab: OpenAI API

Lecture 21 Hugging Face Fundamentals

Lecture 22 Fundamentos de LangChain

Lecture 23 Modelos LLM de código abierto

Section 8: Sust_Hugging Face: The GitHub of language models.

Lecture 24 Introduction to Hugging Face and its components

Lecture 25 Hugging Face interface and model and dataset selection

Lecture 26 Pipelines de Hugging Face

Lecture 27 Tokenizer and Hugging Face Models

Lecture 28 Datasets de Cara de abrazo

Section 9: Open-source Large Language Models (LLMs)

Lecture 29 Benefits of open-source LLM models

Lecture 30 Different open-source LLM models and comparative analysis

Section 10: Giving Superpowers to LLMs with LangChain

Lecture 31 Introduction to LangChain

Lecture 32 LangChain use cases and components

Lecture 33 Different LangChain model types and requirements

Lecture 34 LLM input management with LangChain's Prompts Module

Lecture 35 Combination of LLM with other components through chains

Lecture 36 Providing access to external data through LangChain Indexes

Lecture 37 Giving the ability to memorize ChatGPT through Memor LangChain

Lecture 38 Providing access to tools through LangChain's Agents module

Section 11: Train ChatGPT with a customized knowledge base

Lecture 39 Introduction to LangChain indexes

Lecture 40 Practical Lab: ChatGPT training with PDF data

Section 12: Langchain and Agents: Giving new capabilities to LLMs

Lecture 41 LangChain Agents and Components

Lecture 42 Hands-on Lab: Programming the Wikipedia agent, Google S

Lecture 43 Hands-on Lab: Integration of agents in ChatGPT

Section 13: Working with Open-source models: ChatGPT4All

Lecture 44 ClosedAI y modelos LLM de código abierto

Lecture 45 GPT4ALL Fundamentals

Lecture 46 Hands-on Lab_First steps with GPT4ALL

Lecture 47 Practical Lab_Data privacy with GPT4ALL

Lecture 48 Practical Lab_ Chaining Prompts with GPT4ALL and LangChain e

Lecture 49 Advanced Practical Laboratory_Integration of an external database

Lecture 50 Lab Pr Ava_Generating a vector DB with Alpaca and LangChain eng

Lecture 51 Lab Pract Ava_QnA with GPT4ALL and FAISS vector database

AI enthusiasts eager to learn about the next big thing.,Developers wanting to incorporate LLMs into their tools,Entrepreneurs looking to leverage AI for innovative solutions,Students, educators, and researchers in AI and NLP fields