198839 VU Linear Algebra for Data Scientists
winter semester 2021/2022 | Last update: 10.06.2021 | Place course on memo listUpon successful completion of the course, students understand selected mathematical concepts related to Linear Algebra. They are able to apply these concepts for addressing a large class of data science problems.
The course covers an essential set of Linear Algebra concepts directly useful for modeling and adressing a large class of data science problems. It encompasses topics such as eigenvalues, eigenvectors, quadratic forms, matrix decompositions, inverse and pseudo-inverse, Gram matrices and Principal Component Analysis (PCA). The concepts are presented from the practical perspective in the context of data science and computer programming.
The course consists of lecture and hands-on exercises to solve either alone or in pairs applying new skills with the help of the lecturer.
Course assessment is based on a regular contribution by participants instead of examinations. There are no grades, only a note on "successfully completed" (de: Mit Erfolg teilgenommen) or "not completed" (de: Ohne Erfolg teilgenommen) course. Further assessments details will be provided in the first unit.
This will be announced at the first slot.
Knowledge on vector and matrix algebra is highly recommended. In particular the matrix product and the notion of inverse matrix.
This intermediate-level course introduces mathematical notions and tools for addressing data science related problems that involve Linear Algebra concepts. The focus is on the applications, and the content relies mainly on examples. It is dedicated to all bachelor and master students from study programmes with a basic background on vector algebra and matrix algebra. Take a short self-test to check your skills and get our recommendations.
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Group 1
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Date | Time | Location | ||
Mon 2021-11-15
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08.15 - 11.00 | eLecture - online eLecture - online | ||
Mon 2021-11-22
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08.15 - 11.00 | eLecture - online eLecture - online | ||
Mon 2021-11-29
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08.15 - 11.00 | eLecture - online eLecture - online | ||
Mon 2021-12-06
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08.15 - 11.00 | eLecture - online eLecture - online | ||
Mon 2021-12-13
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08.15 - 11.00 | eLecture - online eLecture - online |