This repository contains all the material for the DEC Python training. This training is developed by DIME and DECID.
This training is structured into three parts. Part 0 is a single-session introduction for people with no coding background. Part 1 is a course that covers the foundations of Python used in almost any type of Python data science project. Part 2 is a collection of stand-alone sessions that assumes knowledge in the foundations of Python and each session dives deeper into the advanced topic.
- Part 0 - Intro to Programming
- Part 1 - Foundations of Data Science in Python
- Session 1 - Variable types and Python syntax
- Session 2 - Control flow and functions
- Session 3 - NumPy and Pandas
- Session 4 - APIs and introduction to data visualization in Python
- APIs
- Data visualization
- Project 1 - Schelling model
- Project 2 - Raster data analysis and ML inference
- Part 2 - Advanced topics of Data Science of Python
- Geospatial analysis
- Introduction to text analysis
- Introduction to data pipelines
- Part 3 - Content in other languages
- Some of the contents of this training have been translated to other languages for workshops with external counterparts. All materials in other languages are archived in this folder.
- Introduccion a Python para ciencia de datos y analisis de textos
- Sesion 1: Tipos de variables y sintaxis
- Sesion 2: Control de ejecucion y funciones
- Sesion 3a: Paquetes y preparacion de datos con pandas
- Sesion 3b: Visualizacion de datos
- Sesion 4a: Estructuracion de datos de texto no estructurados
- Sesion 4b: Limpieza de datos de textos
- Sesion 5: Analisis de textos
We welcome your contributions to this project! Please read our Contributing Guide for details on our Code of Conduct and the process for submitting pull requests.
This project is licensed under the MIT License together with the World Bank IGO Rider. The Rider is purely procedural: it reserves all privileges and immunities enjoyed by the World Bank, without adding restrictions to the MIT permissions. Please review both files before using, distributing or contributing.
Please use the citation suggested in CITATION.cff. Find the APA and BIBTeX formats in the right hand side menu of the landing page of this project's repository.
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