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The Origins Data Science Lab (ODSL) is organizing two block courses on data science topics.
The courses, as well as the tutorials, will take place online. The tutorials will be organised through breakout rooms, each assigned to a tutor.
The block courses follow the schedule:
The course itself, as well as one tutorial will be recorded, the other tutorials not. If you have any objections to this, please contact us directly. We will make the recordings of the lectures available online.
All exercises will be made available before the courses and the deadline to hand in the report is March 31.
They should be sent to: jakob.knollmueller [AT] tum.de
Zoom link: https://tum-conf.zoom.us/j/65666587594 (Passcode: 578388)
Also, the recordings of the lectures and tutorial sessions will be made available.
For students successfully completing both Block Courses, 5 (TUM) or 3 (LMU) ECTS points will be awarded. Formally this is a TUM event, but LMU students can hand in their certificates and it will be recognised.
Successful completion means turning in solutions to assigned problems by the end of March and getting a passing grade. The Courses are:
Update 28.02.: We removed one of the homework exercises for the first block, please make sure to work on the the updated problem sheet.
The recordings of the lecture can be found here:
https://tum.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx?folderID=a188f1f5-e7be-4a84-8461-ae4a009c1acb
Lecturer: Jakob Knollmüller
In this course we will introduce the basic concepts of reasoning under uncertainty. After a brief introduction to probability theory and commonly used probability distributions, we discuss inference tasks with various probabilistic models. We conclude by outlining methods to approach more involved inference tasks through approximation or sampling.
Lecturer: Prof. Lukas Heinrich
In this course we will expand on probability theory and statistical data analysis from the last prior week: After an initial review of probability and the properties of random variates, we will discuss statistical inference approaches comparing and contrasting Bayesian and Frequentist points of view. In the latter framework, we will introduce parameter and interval estimation as well as develop hypothesis testing and interval estimation techniques in the presence of nuisance parameters. The material will be discussed using a number of example scenarios common in the natural sciences.
It is possible to get a Certification or ECTS points for participation in the Block Courses:
To get a Certificate of Participation (for either one of the two blocks or both), you will need to turn in solutions to the exercises that will be assigned during the course (tutoring session exercises) and get a passing grade. The certification will be done on a course-by-course basis, and will state that you have successfully completed the Block Course in the respective topic. Please register for the course in advance so we can estimate how much work will be involved in the evaluation of the reports.
To get the 5 (TUM) or 3 (LMU) ECTS points, you will need to turn in solutions to all exercises for both Block Courses (tutoring + homework exercises) that will be offered this year. The grade for the course will be based on the two sets of exercises, and there will not be an additional exam. The deadline to hand in the report is March 31. Please register for the courses in advance so we can estimate how much work will be involved in the evaluation of the reports.
Participants who do not want a certificate or points are not required to turn in solutions, but are allowed to.