ChatGPT para ciencia de datos y aprendizaje automático en Python

Resumen

Master Data Analysis, Regression, Classification, Clustering and Pandas Coding with ChatGPT! A Project-based Course.

What you'll learn:

Use ChatGPT for real-life Data Science and Machine Learning ProjectsLet ChatGPT write do the Coding work (Python, Pandas, scikit-learn etc.)Use ChatGPT to select the most suitable Machine Learning ModelUse ChatGPT to analyse and interpret the outcomes of Machine Learning & Statistical ModelsPerform an Explanatory Data Analysis with ChatGPT and PythonUse ChatGPT for Data Manipulation, Aggregation, advanced Pandas Coding & moreUse ChatGPT to fit and evaluate Regression and Classification ModelsUse ChatGPT for Multiple Regression Analysis and Hypothesis TestingUse ChatGPT for Error Handling and TroubleshootingMaster Clustering and Unsupervised Learning with ChatGPT **Updated:

Now including the latest models GPT-4o and GPT-4o mini**Welcome to the first Data Science and Machine Learning course with ChatGPT. Learn how to use ChatGPT to master complex Data Science and Machine Learning real-life projects in no time!

Why is this a game-changing course?Real-world Data Science and Machine Learning projects require a solid background in advanced statistics and Data Analytics. And it would be best if you were a proficient Python Coder.

Do you want to learn how to master complex Data Science projects without the need to study and master all the required basics (which takes dozens if not hundreds of hours)? Then this is the perfect course for you!

What you can do at the end of the course:

At the end of this course, you will know and understand all strategies and techniques to master complex Data Science and Machine Learning projects with the help of ChatGPT! And you don´t have to be a Data Science or Python Coding expert!

Use ChatGPT as your assistant and let ChatGPT do the hard work for you! Use ChatGPT forthe theoretical part Python codingevaluating and interpreting coding and ML resultsThis course teaches prompting strategies and techniques and provides dozens of ChatGPT sample prompts toload, initially inspect, and understand unknown datasets clean and process raw datasets with Pandasmanipulate, aggregate, and visualize datasets with Pandas and matplotlibperform an extensive Explanatory Data Analysis (EDA) for complex datasetsuse advanced statistics, multiple regression analysis, and hypothesis testing to gain further insightsselect the most suitable Machine Learning Model for your prediction tasks (Model Selection)evaluate and interpret the performance of your Machine Learning models (Performance Evaluation)optimize your models via handling Class Imbalance, Hyperparameter Tuning & more.evaluate and interpret the results and findings of your predictions to solve real-world business problemsmaster regression, classification, and unsupervised learning/clustering projectsWe´ll cover prompting strategies and tactics for GPT-3.5 / GPT-4o mini (free) and GPT-4 / GPT-4o (paid subscription).

Know the differences and master both!The course is organized into Do-it-yourself projects with detailed project assignments and supporting materials. At the end, you will find a video sample solution.

All solutions and sample prompts are available for simple download or copy/paste! Who is this Course for?Data Science Beginners who have no time to learn everything from scratchSkilled Data Scientists seeking to outsource the most time-consuming parts of their work to save time Are you ready to be at the forefront of AI in Data Science?

Enroll now and start transforming your professional landscape with AI and ChatGPT!

Programa

• Introducción a la IA y Modelos GPT
Visión general de la IA en ciencia de datos y aprendizaje automático
Introducción a los modelos GPT de OpenAI
Comprender la evolución de GPT-3 a GPT-4o
• Configuración del Entorno
Instalación de Python y bibliotecas esenciales
Configuración de un Jupyter Notebook para ciencia de datos
Acceso a la API de OpenAI con claves API
• Fundamentos de ChatGPT
Comprender la arquitectura de GPT-4o
Exploración de GPT-4o mini: Casos de uso y limitaciones
Fundamentos de tokenización y modelado del lenguaje
• Uso de ChatGPT para Ciencia de Datos
Preprocesamiento de datos con GPT
Análisis de texto y tareas de PLN usando GPT
Generación de insights a partir de conjuntos de datos usando generación de lenguaje natural
• Aplicaciones en Aprendizaje Automático
Ingeniería de características con ChatGPT
Uso de ChatGPT para la augmentación de datos
Automatización del etiquetado y anotación de datos
• Construcción de Modelos Mejorados con GPT
Diseño de experimentos con ChatGPT
Interpretación y depuración de modelos usando explicaciones en lenguaje natural
Ajuste fino de modelos de aprendizaje automático con la asistencia de GPT
• Temas Avanzados
Integración de modelos GPT-4o dentro de flujos de datos
Exploración del aprendizaje por refuerzo con modelos GPT
Consideraciones éticas y limitaciones del uso de GPT en ciencia de datos
• Proyectos Prácticos
Construcción de un chatbot conversacional para consultas de datos
Análisis de conjuntos de datos grandes usando GPT para análisis exploratorio de datos
Creación de una herramienta de informes automatizada impulsada por GPT
• Conclusión y Direcciones Futuras
Tendencias futuras en IA y modelos de lenguaje
Educación continua y recursos para avances en IA
• Revisión del Curso y Preguntas y Respuestas
Resumen de conceptos clave
Sesión abierta para preguntas y resolución de problemas

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Impartido por

Alexander Hagmann

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Materias

Data Science