Sección 1 Temas Selectos de Análisis Numérico y Computación Científica: Computo científico para el análisis de datos

Curso del posgrado conjunto en Ciencias Matemáticas PCCM UNAM UMICH 2024-2

1.1 Temario

  1. Git y Github

  2. Shell

  3. Python

  4. SQL

  5. Power BI

  6. R

  7. Estadística multivariada

  8. Análisis de regresión

1.2 Referencias

[1] Arnold, Jeremey. Learning Microsoft Power BI, O’Reilly Media, Inc.

[2] Beaulieu, Alan. Learning SQL, O’Reilly Media, Inc., 2020

[3] Bruce, Peter, Bruce, Andrew and Gedeck, Peter. Practical Statistics for Data Scientists, O’Reilly Media, Inc., 2020.

[4] Crawley, Michael J. The R book. John Wiley & Sons, 2012.

[5] McKinney, Wes. Python for data analysis. O’Reilly Media, Inc., 2022.

[6] Nelli, Fabio. Python Data Analytics, Apress.

[7] Wade, Ryan. Advanced Analytics in Power BI with R and Python, Apress.

[8] Wickham, Hadley, and Garrett Grolemund. R for data science: import, tidy, transform, visualize, and model data. O Reilly Media, Inc., 2016.

[9] Zamora Saiz, Alfonso, et al. An Introduction to Data Analysis in R: Hands-on Coding, Data Mining, Visualization and Statistics from Scratch., Springer (2020).

[10] Software Carpentry, The Unix Shell, https://swcarpentry.github.io/shell-novice/

[11] Scientific Python Lectures

[12] ASPP Latam

1.4 DataCamp

DataCamp
DataCamp