EdX

Analizando datos con Python (edX)

Offered by IBM,
Analizando datos con Python (edX)

En este curso aprenderás cómo analizar datos en Python usando matrices multidimensionales en numpy, a manipular DataFrames en pandas, a usar la biblioteca SciPy de rutinas matemáticas y a realizar aprendizaje automático usando scikit-learn.

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Aprende a analizar datos usando Python en este curso introductorio. Pasarás de comprender los conceptos básicos de Python a explorar muchos tipos diferentes de datos a través de clases, laboratorios prácticos y tareas. ¡Aprenderás cómo preparar datos para el análisis, realizar análisis estadísticos simples, crear visualizaciones de datos significativas, predecir tendencias futuras a partir de datos y más!
Ten en cuenta que los foros de discusión de este curso están abiertos para que los estudiantes publiquen y se comuniquen entre sí. Sin embargo, los foros ya no serán supervisados por el equipo de IBM. Las preguntas técnicas relacionadas con tu experiencia en el curso deben dirigirse al equipo de soporte de edX a través de la información de contacto proporcionada en el curso. Gracias.
This course is part of the Ciencia de datos con Python Professional Certificate and IBM: Ciencia de datos Professional Certificate.
What you'll learn

  • Cómo importar conjuntos de datos, limpiar y preparar datos para el análisis, resumir datos y construir canalizaciones de datos
  • Cómo utilizar Pandas DataFrames, matrices multidimensionales Numpy y bibliotecas SciPy para trabajar con varios conjuntos de datos
  • Cómo cargar, manipular, analizar y visualizar conjuntos de datos con pandas, una biblioteca de código abierto
  • Cómo crear modelos de aprendizaje automático y hacer predicciones con scikit-learn, otra biblioteca de código abierto

Incluye las siguientes partes:
Bibliotecas de análisis de datos: aprenderás a usar Pandas DataFrames, matrices multidimensionales Numpy y bibliotecas SciPy para trabajar con varios conjuntos de datos. Te presentaremos pandas, una biblioteca de código abierto, y la usaremos para cargar, manipular, analizar y visualizar conjuntos de datos geniales. Luego, te presentaremos otra biblioteca de código abierto, scikit-learn, y utilizaremos algunos de sus algoritmos de aprendizaje automático para construir modelos inteligentes y hacer predicciones geniales.

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