En este curso aprenderás los fundamentos de la extracción, transformación y carga (ETL) de datos, así como la exploración de datos en la ciencia de datos. Aprenderás a trabajar con Pandas y dataframes, a leer archivos CSV y XLSX, y a comprender los conceptos de series temporales. Además, aprenderás la visualización de datos utilizando Matplotlib, creando gráficas individuales y personalizadas. También utilizarás NumPy y la manipulación de arrays, realizando las operaciones básicas y calculando gradientes. A lo largo del curso, desarrollarás buenas prácticas en el flujo de trabajo en ciencia de datos y en los conceptos avanzados como multi-índices en series temporales. Finalmente, sabrás como usar paquetes para uso local.
Python: de usuario a explorador de datos
Python: de usuario a explorador de datos
Taught in Spanish
Beginner level
No prior experience required
16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace
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There are 5 modules in this course
What's included
21 videos1 reading1 programming assignment
What's included
14 videos1 programming assignment
What's included
16 videos1 programming assignment
What's included
16 videos1 programming assignment
What's included
2 videos1 programming assignment
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