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BoringoDavid/DCIBI-Journey

Domain:

education

Record type:

project
Creator:
Bor
Host:
Data Science from AIMS Rwanda # Data Science Capacity Building Initiative (DSCBI) This repository provides information about the capacity building initiative, a collaboration between the African Institute for Mathematical Sciences (AIMS), the National Institute of Statistics of Rwanda (NISR), and Cenfri. The initiative aims to deliver data science training to staff from over 20 institutions that are part of Rwanda's National Statistical System (NSS). This repository provides information about the capacity building initiative, a collaboration between the African Institute for Mathematical Sciences (AIMS), the National Institute of Statistics of Rwanda (NISR), and Cenfri. The initiative aims to deliver data science training to staff from over 20 institutions that are part of Rwanda’s National Statistical System (NSS). ## Course Modules The training program is structured around the following core modules: 1. **Python Foundations for Data Science** Covers core and advanced Python programming, object-oriented design, development tools, Git/GitHub workflows, Python packaging, and best practices for maintainable code. 2. **Data Analysis with Python** Focuses on cleaning, transforming, and analyzing structured data using pandas and polars, with applications to real-world datasets like census and surveys. 3. **Working with Spatial Data in Python** Introduces geospatial data handling using GeoPandas, shapely, and rasterio; includes spatial joins, projections, and mapping access to services. 4. **Working with Time Series Data in Python** Covers handling temporal data, resampling, rolling windows, time series decomposition, and forecasting using statsmodels and Prophet. 5. **Databases and APIs** Introduces SQL and relational databases, extracting and analyzing data from APIs, and building REST APIs with FastAPI. 6. **Introduction to Machine Learning with Scikit-learn** Provides foundations in supervised and unsupervised learning, including models like logistic regression, decision trees, and PCA, …

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