Python para Data Science & Machine Learning en 18 Días

Data Science extremo con Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn, Tensorflow, Machine Learning, y todo lo demás
4.77 (2172 reviews)
Udemy
platform
Español
language
Data Science
category
Federico Garay
instructor
Python para Data Science & Machine Learning en 18 Días
11 561
students
25.5 hours
content
Mar 2025
last update
$94.99
regular price

What you will learn

Aplicarás el Data Science en proyectos de manipulación compleja de información.

Escribirás código Python de manera global, con confianza y comodidad

Usarás Pandas para limpiar, transformar, y analizar grandes conjuntos de datos

Dominarás NumPy para operaciones matemáticas y estadísticas sobre grandes arrays de datos

Crearás visualizaciones atractivas y reveladoras con Matplotlib, Seaborn y Sci-kit Learn

Harás predicciones usando algoritmos de Machine Learning

Usarás Tensorflow para implementar redes neuronales y Deep Learning

Desarrollarás habilidades para el Análisis Exploratorio de Datos (EDA)

Al finalizar, serás capaz de recibir una tonelada de datos, y devolver visualizaciones interesantes, que ayuden a tus clientes a tomar decisiones relevantes.

Serás una persona con el potencial de hacer de nuestro mundo un lugar mejor.

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Our Verdict

Federico Garay's 'Python para Data Science & Machine Learning en 18 Días' offers an engaging and thorough learning experience in the realms of Data Science, Machine Learning, and related tools through practical examples in Python. Although it demands dedication from learners with fast-paced content delivery, those committed will acquire data analysis expertise backed by hands-on practice and curated resources to support their journey.

What We Liked

  • Comprehensive coverage of Data Science & Machine Learning tools with 25.5 hours of content
  • Engaging teaching style and daily practical exercises by an experienced Udemy instructor
  • Curated resources like code files, databases, and cheat sheets for better understanding
  • Includes popular libraries such as NumPy, Pandas, TensorFlow, Scikit-Learn, & more

Potential Drawbacks

  • Jupyter Notebooks setup might be challenging for some learners in the beginning phase
  • Concepts are presented quite fast, which can overwhelm beginners with no prior exposure to Python
  • Lack of closed captions and interactive discussions on certain complex topics
  • Some content and library versions may require occasional updates
5702682
udemy ID
10/12/2023
course created date
05/05/2024
course indexed date
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course submited by
Python para Data Science & Machine Learning en 18 Días - | Comidoc