Online Course on Cloud Computing and algorithms for EO analyses

EO AFRICA R&D Facility Online Course

Cloud Computing and algorithms for EO analyses

Introduction to the course

This course introduces participants to Cloud Computing and its usage for Earth Observation (EO) data analyses. It starts with big geospatial data concepts and extends to Cloud Computing as one of the solutions for solving the problems of big EO data.

The EOAFRICA Facility Innovation Lab will be introduced as an example of a cloud computing platform for working with EO data. We will cover Jupyter Notebooks and JupyterLab as the proper solution for developing analytical procedures accompanied with documentation on cloud computing platforms.

The course focuses on some of the Python libraries to develop programs that handle and analyze EO data. We will explain how participants can programmatically access different EO datasets using online catalogue services and utilize the data in their algorithms. Particularly, we explain the key features and recent developments of openEO platform for EO data analyses.

Participants apply the knowledge and skills gained on a final project using EO data available on the Innovation Lab.

This course will provide participants with:

  • An understanding of Cloud Computing and its benefits for EO (Earth Observation) analysis.
  • A comparison of various cloud computing platforms.
  • Hands-on experience with the Innovation Lab, the cloud computing platform offered by the EO AFRICA R&D Facility.
  • Hands-on experience with key Python libraries for EO data processing.
  • The ability to implement processing workflows through interactive Jupyter Notebooks on the Innovation Lab.
  • Knowledge on how to load and process EO data from DIAS platforms.
  • The capability to load and process EO data using Python libraries.
  • Hands-on experience in implementing Python-based workflows on openEO platform.

Mode of Delivery

The course has limited interactive online sessions, recorded videos, exercises, and reading materials. All the live sessions will be recorded and provided to the participants. The course also includes project activities, during which support and advice will be provided. The total study load is estimated to be 40 hours (10 hours per week).

Prerequisites

The participants need to have basic programming skills in Python.

Selection

The course will be offered to a maximum of 75 participants. Selection will be based on relevant academic background and employment. Only applicants working for an African-based organization are eligible. We will strive to have a gender-balanced and country-balanced group of participants. Preference is given to candidates working as (Ph.D.-) researchers, post-docs, and university staff. Selection will be made two weeks before the course starts. Participants are advised to notify their employer or institution about their commitment to this online course.

Timeline:

The online course will have sessions on:

  • Monday, November 11 at 14:00 CET: The kick-off session
  • Wednesday, November 13
  • Monday, November 18
  • Wednesday, November 20
  • Monday, November 25
  • Wednesday, November 27
  • Monday, December 2

The detailed program timing of interactive sessions will be communicated later.

Registration:

Teachers: