Poor air quality has become a concern in Africa, but data are scarce on different air pollutants. Nevertheless, owing to technological progress observed in the last few decades, small scale air sensors are being considered as a promising technology to generate the missing data. Generated data could be massive and therefore require specific skills to manipulate them and get their full understanding.
This course on air quality data analysis organized under the umbrella of the ASAQ aims to empower participants with the skills necessary to manage and analyze air quality data effectively. This initiative is crucial, given the increasing awareness of air pollution and the need for reliable data to inform policy decisions.
Course Overview
- Target audience: students, researchers, policymakers, and environmental activists.
- Objectives: Equip participants with skills in data analysis and interpretation to support air quality management efforts.
- Outcome: At the end of this course, participants will be able to use Python to read their (time series and geolocated) data files, inspect their data, perform basic data cleaning tasks, generate statistics, track the movement of objects, create static and interactive maps. Participants will also learn how to use Jupyter notebook in a cloud platform.
- Schedule: Monday, January 20 to Friday, January 24 (12:00 - 13:30 UTC)
Key Topics
- Core tools for Data Science: NumPy, Matplotlib, Pandas, Seaborn, SciPy
- Data Analysis: Reading, manipulating and visualizing data with Pandas, GeoPandas and MovingPandas
Registration
Dates: December 10, 2024 - January 10, 2025
Participation in this course is totally free of charge!
All participants are required to have a Gmail account.
Please note that there is no certificate for this course.
For any inquiries or questions, please contact Dr. Bertrand Tchanche (bertrand.tchanche[@]uadb.edu.sn).
