Interested in disaster risk management? Curious about how you can use Deep Learning models to monitor potential disasters? This free, self-paced, online course developed by NVIDIA Deep Learning Institute jointly with the United Nations Satellite Centre (UNOSAT) is for you!

The course teaches participants to build and deploy a deep learning model built with different frameworks which uses satellite imagery to detect natural disasters – specifically flood events. The use of deep learning models for disaster risk management are advantageous because they lower costs, increase efficiency and increase effectiveness of disaster risk monitoring.


In order to take part in this course, participants must already be competent in Python 3 programming language. They are also required to have a basic understanding of Machine Learning and Deep Learning concepts and pipelines, as well as interest in manipulating satellite imagery.

Learning outcomes

By taking part in this course, participants will learn:

  • Implementing a machine learning workflow for disaster management solutions
  • Processing large satellite imagery data using hardware accelerated tools
  • Cost-efficiently build deep learning segmentation models by applying transfer-learning
  • Using deep learning models for real-time monitoring and analysis
  • Detecting and responding to flood events by using deep learning-based model inference



Source : European Digital Skills & Jobs Platform


Competence Area

Information and data literacy


  • Information systems
  • Databases
  • Advanced technologies (AI, blockchain, IoT, big data etc.)

Digital technology / specialisation

  • Machine Learning

Digital skill level

  • Advanced
  • Digital Expert

Geographic Scope - Country

  • European Union
  • Non-EU

Type of initiative

International initiative

Target audience

  • Digital skills for ICT professionals and other digital experts.
  • Digital skills for all

Target language

  • English

Target group

  • High Achievers
  • Persons who have completed tertiary education (EQF 7)
  • Persons with 0-3 years work experience
  • Persons who have completed tertiary education (EQF 8)
  • Persons with 3-10 years work experience
  • Persons with 10+ years work experience
  • Persons who have completed tertiary education (EQF 6)

Typology of training opportunities


Training duration

Up to 4 weeks

Credential offered