IA generativa: API de OpenAI, DeepSeek y ChatGPT en Python

Resumen

Empower Your Business With GenAI, Artificial Intelligence, GPT-4o, o1, o3, DeepSeek, and More! What you'll learn:

How to setup and use the OpenAI API with ChatGPTHow to effectively use prompt engineeringRAG (retrieval-augmented generation) with the OpenAI Embeddings APIFAISS (Facebook AI Similarity Search)How to Fine-Tune ChatGPT Welcome to the forefront of artificial intelligence with our groundbreaking course on Generative AI (GenAI), the OpenAI API, DeepSeek, and ChatGPT.

With ChatGPT and DeepSeek, you'll learn how to build with the world's most advanced Large Language Models (LLMs). This course is a must-have if you want to know how to use this cutting-edge technology for your business and work projects.This course contains 5 main sections:

Basic API Usage:

All the fundamentals:

signup for an account, get your API key, set environment variables on Windows / Linux / Mac, using the API in Python, setup billing, understand the pricing model, and OpenAI's usage policies.

Of note is the chatbot tutorial, which goes over how to incorporate chat history into the model so that ChatGPT "remembers" what it said to you previously. A customer service chatbot will serve as a running example throughout this course.Prompt Engineering:

ChatGPT Prompt Engineering for Developers - All about how to make ChatGPT do what you want it to do.

We'll explore various example use-cases, such as getting ChatGPT to output structured data (JSON, tables), sentiment analysis, language translation, creative writing, text summarization, and question-answering. We'll explore techniques like chain-of-thought (CoT) prompting, and we'll even look at how to use ChatGPT to build a stock trading system!Retrieval Augmented Generation (RAG):

Learn how to incorporate external data into LLMs.

This powerful technique helps mitigate a common problem called "hallucination". It's critical if you have proprietary data (like product info for your company) that your LLM doesn't know about.

You'll learn how semantic search / similarity search works, and how to implement it using FAISS (Facebook AI Similarity Search library). Learn how this will allow you to "chat with your data".Fine-Tuning:

Learn how to "train" an LLM on your own dataset so that it behaves the way you want it to.

Sometimes prompt engineering and RAG won't cut it.GPT-4 with Vision:

Everything in this course can be done with GPT-4, but what makes GPT-4 (and GPT-4 Turbo) special is its vision capabilities. That is, it can understand images.

In this section, we'll explore many of the amazing applications of combined text-image understanding, some of which include automated homework grading, explaining memes and humor, handwriting transcription, web development, game development, and writing product descriptions based on images (business owners - you already know how this will skyrocket your productivity).Throughout this course, you'll engage in hands-on exercises, real-world applications, and expert guidance to solidify your understanding and mastery of generative AI concepts. Whether you're a seasoned developer, aspiring AI enthusiast, or industry professional, this course offers a transformative experience that will empower you to harness the true potential of AI.Are you ready to embark on this exhilarating journey into the future of AI?

Join us and unlock the endless possibilities of Generative AI today!Suggested Prerequisites:

Python coding

Programa

• Introducción al Curso
Resumen y objetivos del curso
Requisitos previos y requerimientos
• Uso Básico del API
Configuración de una cuenta en OpenAI y obtención de una clave API
Configuración de variables de entorno (Windows/Linux/Mac)
Uso del API de OpenAI en Python
Configuración de facturación y comprensión del modelo de precios
Resumen de las políticas de uso de OpenAI
Creación de un chatbot de servicio al cliente con historial de chat
• Ingeniería de Prompts
Conceptos básicos de prompts y mejores prácticas
Casos de uso: salida en JSON, tablas, análisis de sentimientos
Traducción de idiomas y escritura creativa
Resumen de texto y respuestas a preguntas
Prompts de cadena de pensamiento (CoT)
Desarrollo de un sistema de comercio de acciones con ChatGPT
• Generación Aumentada con Recuperación (RAG)
Introducción a RAG e incorporación de datos
Mitigación de alucinaciones en modelos de IA
Conceptos de búsqueda semántica y búsqueda por similitud
Implementación de RAG usando FAISS (Facebook AI Similarity Search)
Aplicaciones: "Chatea con tus datos"
• Ajuste Fino
Resumen y beneficios del ajuste fino
Entrenamiento de un LLM con conjuntos de datos personalizados
Limitaciones y cuándo usar ajuste fino sobre ingeniería de prompts
• GPT-4 con Visión
Introducción a las capacidades de visión de GPT-4
Aplicaciones de comprensión de texto e imagen
Calificación automatizada de tareas y explicación de memes
Transcripción de escritura a mano
Desarrollo web y de juegos
Creación de descripciones de productos a partir de imágenes
• Ejercicios Prácticos y Aplicaciones del Mundo Real
Proyectos prácticos y ejercicios
Ejemplos y estudios de caso del mundo real
• Conclusión y Próximos Pasos
Resumen de aprendizajes clave
Recursos para aprendizaje y exploración adicional
Retroalimentación y cierre del curso

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Impartido por

Lazy Programmer Inc. and Lazy Programmer Team

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Materias

Computer Science