Data Science for Urban Mobility
- Lectures: Wednesday 10:15, Narva mnt 18, r-2034.
- Practicals: Friday 10:15, Narva mnt 18, r-2034.
- Lecturer: Amnir Hadachi (email@example.com)
- Lab Assistant: Artjom Lind (firstname.lastname@example.org)
- This semester the course will be in a hybrid format for the lab session and for the lecturers' in the format of live stream and recordings.
- You will receive an email before each session with details.
- Wednesday at 10:15,
More details about the lectures are in the lectures section.
- Friday at 10:15,
To take advantage of the lab session, we suggest you check the lab material before attending the online sessions.
The rapid development of Data Science and especially the consulting engagement at a high level has made the job market in need of such skilled professionals in the transportation field. This course will help students to gain knowledge about nowadays problems in urban mobility and how to use Data Science skills to convey in the right manner in defining the appropriate questions, understanding the limitation, and finding suitable solutions.
For this reason, the course is designed to help students to understand the relevance and limitations of data-centric approaches when applied to urban transport in contrast to other methods, such as modeling and forecasting. Furthermore, the course will provide the students with the knowledge required to use Data Science to solve Urban Mobility problems, covering all the traditional steps from data to insight discovery.
This class will include but not limited to the following topics:
- Introduction Data Science, Big data, and Python
- Data Preparation
- Spatial Data
- Bayesian Inference
- Machine Learning
- Spatial Analysis
- Data Visualization
- Professional issues and ethics
- Critical messages will be announced personally using ÕIS
- Course general discussion will happen on Course forum board: [ Group Forum ]
- Access granted during the first week