No-code AI applications with ChatGPT, OpenAI, Flowise & LLMs

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Data Bootcamp

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1. Introduction to Language Models

1. Introduction to Language Models.mp4

03:21

2. What are Language Models.mp4

03:28

3. Types of Language Models.mp4

03:38

2. Introduction to ChatGPT

1. OpenAI, the company behind the ChatGPT algorithm.mp4

03:03

2. Introduction to ChatGPT.mp4

03:00

3. Advantages of ChatGPT and difference with conventional ChatBots.mp4

03:25

4. Limitations of ChatGPT.mp4

03:14

3. Tools for LLM and NLP

1. Tools for working with LLMs and NLPs.mp4

02:19

2. Open AI API.mp4

06:00

3. Hands-on Lab OpenAI API.mp4

06:00

4. Hugging Face Fundamentals.mp4

05:19

5. LangChain Fundamentals.mp4

03:41

6. Open-source LLM models.mp4

04:31

4. AI Application Development with ChatGPT with LangChain

1. Introduction to LangChain.mp4

03:22

2. Different LangChain model types and requirements.mp4

06:41

3. LLM input management with LangChains Prompts Module.mp4

04:30

4. Combination of LLM with other components through chains.mp4

02:51

5. Providing access to external data through LangChain Indexes.mp4

02:36

6. Giving ChatGPT the ability to memorize through the LangChain Memory.mp4

01:57

7. Providing access to tools through LangChains Agents module.mp4

02:11

5. Application Development with ChatGPT without code with Flowise

1. Developing state-of-the-art LLMs.mp4

04:29

2. Flowise Features.mp4

02:38

3. Installation of Flowise.mp4

02:47

4. Getting started with Flowise.mp4

05:35

6. Flowise components

1. Flowise components.mp4

04:27

2. Flowise Modeling Component.mp4

03:22

3. Flowise Prompts Component.mp4

02:35

4. Vector Stores, Indices, Embeddings and Document Loaders of Flowise.mp4

05:12

5. Flowise Memory Component.mp4

03:19

6. Flowise Chain Component.mp4

02:37

7. Flowise Agents and Tools.mp4

03:33

7. Flowise Practical Project (Part I)

1. Practical Exercise Designing the customized wizard.mp4

01:43

2. Solution Customized wizard design.mp4

01:55

3. Practical Exercise Basic ChatFlow Development.mp4

00:43

4. Solution Basic ChatFlow Development.mp4

04:06

5. Practical Exercise Development of an Assistant.mp4

01:09

6. Solution Development of an Assistant.mp4

02:24

8. LLM Model Training

1. Different variants of LLMs and how to select them.mp4

04:05

2. Data privacy in ChatGPT training.mp4

04:29

9. LLM training with your own documents

1. Fundamentals of LLM training with documents.mp4

03:42

2. Lab Adding the QA Chain, Vector Store and PDF Loader.mp4

03:40

3. Lab Adding Text Splitter and OpenAI Embeddings.mp4

03:50

10. Vector Databases

1. Introduction to vector databases and importance for LLMs.mp4

03:03

2. Characteristics of vector databases.mp4

03:42

3. Different Vector Databases.mp4

02:01

4. Pinecone Fundamentals.mp4

05:07

5. Adding Pinecone Vector Estore.mp4

03:46

6. Loading Embeddings and Indexes from Pinecone.mp4

03:11

11. Flowise Practical Project (Part II)

1. Practical Exercise Developing Indexes and Embeddings for Pinecone.mp4

00:57

2. Solution Creating Vectors and Indexes in Pinecone.mp4

04:54

3. Practical Exercise Development of a Customized LLM.mp4

00:38

4. Solution Development of a customized LLM.mp4

02:20

5. Practical Exercise Putting into Production.mp4

00:26

6. Solution Production deployment of the Custom LLM.mp4

04:09

12. Multi-stage reasoning

1. Multi-step reasoning.mp4

02:00

2. Linking two large language models (LLM).mp4

04:07

3. Chaining a third language model.mp4

02:50

13. Hugging Face and the integration of Hugging Face in Flowise

1. Introduction to Hugging Face and its components.mp4

04:15

2. Hugging Face interface and model and dataset selection.mp4

03:30

3. Tokenizer and Hugging Face Models.mp4

04:59

4. Hugging Face Datasets.mp4

03:05

5. Practical Lab Use of models from Hugging Face.mp4

03:59

6. Practical Lab Consuming the Hugging Face model from Python.mp4

03:35

7. Practical Laboratory Using Hugging Face models from Flowise.mp4

03:40

14. Open-source Large Language Models (LLMs)

1. Benefits of open-source LLM models.mp4

06:05

2. Different open-source LLM models and comparative analysis.mp4

06:09

3. Fundamentals of the Llama model.mp4

03:21

4. Alpaca model fundamentals.mp4

05:14

5. Fundamentals of the Vicuna model.mp4

04:22

6. Downloading and initialization of the model with Docker, LocalAI and GPT4All.mp4

05:34

7. Using the LLM Open Source model from Flowise.mp4

03:14

8. Advanced Project with Local AI LLama2, Faiss and Local AI Embeddings.mp4

03:36

15. Falcon the most powerful Open-Source model to date

1. Fundamentals of the Falcon model.mp4

02:33

2. Practical Lab Using the Falcon 7b model from Flowise.mp4

03:21

3. Practical Lab Using the Falcon 40b model from Flowise.mp4

03:07

16. Open-Source Cloud Models with Replicate

1. Replicate Basics.mp4

05:12

2. Using LLM Open-source Llama, Vicuna and Falcon through Replicate.mp4

02:24

3. Use of Replicates Llama2 model through Flowise.mp4

02:24

17. Flowise Credentials

1. Credential management in Flowise.mp4

03:14

18. Auto-GPT the AI that outperformed ChatGPT

1. Introduction to Auto-GPT.mp4

04:05

2. Auto-GPT, BabyAGI and Jarvis models.mp4

05:40

3. Practical Lab Using Auto-GPT.mp4

09:40

4. Hands-on Lab Auto-GPT Basics in Flowise.mp4

03:52

5. Hands-on Lab Using Auto-GPT from Flowise.mp4

04:31

6. Baby AGI the evolution of the AutoGPT model.mp4

04:54

19. Putting Flowise models into production

1. Production Deployment of LLMs.mp4

02:30

2. Putting into Production through APIs.mp4

06:25

3. Adding credentials to APIs.mp4

02:58

4. Querying PDF files using Flowise APIs.mp4

03:01

20. Project from start to finish

1. Web Scrapper, Pinecone and Conversational Retrieval QA Chain.mp4

03:25

2. Improving the Web Scrapper and avoiding model hallucinations.mp4

01:59

3. Alternative project configuration.mp4

02:34

Description

Develop ChatGPT and LLM applications without programming skills using ChatGPT, Flowise, LangChain, Llama, Pinecone...

What You'll Learn?

Introduction to Language Models
Tools for working with LLMs and NLPs
AI Application Development with ChatGPT with LangChain
Application Development with ChatGPT and no-code LLMs
Introduction to Flowise and components
Developing state-of-the-art LLMs
LLM Model Training
LLM training with your own documents
Multi-stage reasoning with the string module
Open-source Large Language Models (LLMs)
Credential management in Flowise
Auto-GPT the AI that outperformed ChatGPT

Who is this for?

Any professional who wants to create applications based on ChatGPT without programming ChatGPT

If you are intrigued by the world of AI and wish to create intelligent applications without mastering programming

If you are an entrepreneur looking to capitalize on AI

If you work in a constantly evolving environment and want to incorporate ChatGPT solutions into your workflow without learning to program

What You Need to Know?

No previous programming knowledge is required

More details

Description
In a constantly evolving digital world, Artificial Intelligence has ceased to be a futuristic concept to become an essential tool in various areas of our daily lives. However, the challenge has always been how to make this technology accessible to those who have no programming experience. This is where this course comes to life.

Have you ever wondered how to create intelligent, automated solutions without having to learn to program from scratch? This course is your answer. We offer you a unique opportunity to learn how to develop applications powered by ChatGPT and LLMs without writing a single line of code. Not only do we provide you with access to one of the most revolutionary technologies of the moment, but we give you the ability to design, prototype and launch your own AI-based solutions.

Content Description:
Solid Fundamentals: Start with a clear understanding of Language Models and discover the power behind ChatGPT.
Tools at your fingertips: Learn about cutting-edge tools like LangChain and Flowise that will allow you to bring your ideas to life.
Hands-on projects: Apply your knowledge through practical projects and challenges that guarantee an immersive learning experience.
Future of AI and ChatGPT: Discover Auto-GPT and other cutting-edge models that are defining the next horizon of AI.
There are no longer any barriers between you and next-generation AI applications. Take this opportunity to master ChatGPT and other AI tools, all without having to dive into complex lines of code. Are you ready to transform the future with your own intelligent solutions? Start your journey today!
Who this course is for:
Any professional who wants to create applications based on ChatGPT without programming ChatGPT
If you are intrigued by the world of AI and wish to create intelligent applications without mastering programming
If you are an entrepreneur looking to capitalize on AI
If you work in a constantly evolving environment and want to incorporate ChatGPT solutions into your workflow without learning to program

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Data Bootcamp transforma a los profesionales en expertos de datos al optimizar, simplificar y personalizar la experiencia de aprendizaje en línea.Desde hace años hemos ayudado a estudiantes y equipos en más de 150 países a desarrollar las habilidades de análisis e inteligencia empresarial más buscadas, a través de cursos, evaluaciones de habilidades, rutas de aprendizaje y capacitación empresarial.Aprender nuevas habilidades en el sector del dato es fácil. Data Bootcamp será tu equipo personal de instructores, expertos y mentores que te ayudarán en el proceso de aprendizaje y a desarrollar las habilidades profesionales más demandadas.Nuestro equipo se compone por expertos reconocidos en el campo del data anytics, MVPs, MCTs y expertos certificados de Microsoft.

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