- Lecturer: Mihai Cucuringu
Course Term: Michaelmas
Course Lecture Information: 16 lectures
Course Overview:
Taught by Professor Mihai Cucuringu (Statistics)
Course material will be posted at: http://www.stats.ox.ac.uk/~cucuring/MathCDT.htm
This is a course covering a number of topics in Data Science, that will combine boththeoretical and practical approaches. The goal of the course is, on one hand, to understand (at least at a high level)the mathematical foundations behind some of the state-of-the-art algorithms for a wide range of tasks includingorganization and visualization of data clouds, dimensionality reduction, network analysis, clustering, classification,regression, and ranking. On the other hand, students will be exposed to numerous practical examples drawn froma wide range of topics including social network analysis, finance, statistics, etc.
Course material will be posted at: http://www.stats.ox.ac.uk/~cucuring/MathCDT.htm
This is a course covering a number of topics in Data Science, that will combine boththeoretical and practical approaches. The goal of the course is, on one hand, to understand (at least at a high level)the mathematical foundations behind some of the state-of-the-art algorithms for a wide range of tasks includingorganization and visualization of data clouds, dimensionality reduction, network analysis, clustering, classification,regression, and ranking. On the other hand, students will be exposed to numerous practical examples drawn froma wide range of topics including social network analysis, finance, statistics, etc.
Learning Outcomes:
This is a 16 hour course held in the first two weeks of the CDT in Random Systems