The hybrid training program, available in Kinshasa, is an excellent opportunity for professionals and students interested in urban data management and machine learning. This one-of-a-kind program combines theoretical courses with hands-on workshops, covering critical topics like effective urban data management, cost-effective data collection techniques, and a fundamental introduction to machine learning. Recognized experts in these fields will accompany participants throughout the program, offering valuable advice and guidance.

The course will begin with a presentation of the objectives and the overall structure of the ACL program. Participants will then delve into the heart of the matter with intensive sessions that blend theory and practice.

The first day is dedicated to the understanding of urban data, with a geospatial analyst presenting fundamental aspects such as data typology and their critical role in urban environments. In the afternoon, an urban mobility expert speaks about low-cost data collection methods, emphasizing the importance of innovative techniques such as crowdsourcing and the use of urban data platforms.

The second day focuses on artificial intelligence, specifically machine learning and deep learning, with an emphasis on their application to urban data. The day concludes with a practical workshop in which participants study a real-world case: the spatio-temporal tracking of fooding in an urban setting, putting the concepts learned into practice.

The third day is dedicated to case studies on crowdsourcing techniques and the implementation of dedicated platforms. In the afternoon, the training continues with sessions on machine learning, using platforms such as Google Earth Engine (GEE).

The fourth day focuses on a case study: an analysis of urban sprawl in Kinshasa using GEE in relation to the Objective of Sustainable Development 11.3 (ODD 11.3). In the afternoon, another case study is presented, this time on the analysis of urban accessibility in Kinshasa, using open-source data.

On the fifth and final day, participants conduct a thorough analysis, validate classification models, generate and interpret classification results. This day is critical for consolidating previously acquired skills and applying them practically.

The training concludes with a recapitulation and feedback session, giving participants the opportunity to reflect on what they have learned and discuss future applications of their new skills in the fields of urban data management and artificial learning.

The major advantage of this course is its hybrid approach, which combines theory and practice. Participants benefit from interactive learning with field experts and the opportunity to apply their knowledge to real-world case studies. This method not only improves students' understanding of the concepts covered, but it also provides an immersive learning experience that is directly applicable to their professional or academic settings.

Conditions of participation :

• Completion of the MOOC "Urban data management: the key to developing smarter African cities ".
• Have a minimum of two years' experience in urban planning, geography, urban management, data science or a related field.
• Have basic knowledge of computer tools and modeling techniques.   

How to apply :

Send your application (link to MOOC certificate + CV + short paragraph stating your motivation) to mailto:formations@africancitieslab.org. Please mention "Formation Kinshasa" in the subject line.

Registration closes on February 26, 2024 at 11:59 pm DRC time. 

Number of places available: 25

The 25 successful candidates will receive :

• The training course and all the necessary teaching aids and tools;
• A certificate at the end of the course;
• Snacks and meals during the training week;

Participants are responsible for any travel and accommodation expenses.

Language of training: French