Scientific Data Computing
- Lectures: Monday 16:15, Ulikooli 17, 2-219
- Practicals: Wednesday 10:15, Ulikooli 17, 2-219
- Lecturer: Amnir Hadachi (amnir.hadachi@ut.ee)
Objective
Nowadays the fast development of technologies has made a huge amount of data available. Due to this progress, data has been collected from a variety of sources, such as smartphones, embedded sensors, trade markets, social media, hospitals, or other sources. From this prospective, modeling or conducting scientific computing has become depended on the nature and type of data. In other words, data is shaping the algorithms and scientific computing techniques.
For this reason, the course “Scientific Data Computing” is designed in such a way to make the students understand that the scientific computing and modeling field is driven by data. Therefore, the course will teach you the important algorithms that help to deal with big data, and show how to apply them in real world applications from a scientific computing perspective. One of the objectives of the course is to make the students understand how the nature of data can influence our decisions in selecting the right models or designing the algorithms for specific purposes.
Topics
This class will include but not limited to the following topics:
- Introduction
- Statistical methods and their applications
- Linear algebra and singular value decomposition
- Basic optimization
- Image processing and analysis
- Compressed sensing
- Text processing
- Time series analysis and wavelets
Discussion Board:
- Critical messages will be announced personally using ÕIS
- Course general discussion will happen on Course forum board: [ DS Group Forum ]
- Access granted during the first week