On this webpage you’ll find information about the University of Tartu Institute of Computer Science courses that are looking for student teaching assistants. It’s a great opportunity to share your knowledge with fellow students while honing your teaching skills. Several of the positions are paid. If you have any questions about a particular course, contact the course instructor directly.
Language Technology (LTAT.01.002)
Contact: Krista Liin, krista.liin@ut.ee
Semester: Autumn
Language: Estonian
Tasks: grading homework every 2 weeks, giving feedback to students
Required skills: basic knowledge of Python, AI, NLP. Previous experience with the course is a bonus.
Other important information: remote work.
Language Technology (LTAT.01.002)
Contact: Krista Liin, krista.liin@ut.ee
Semester: Autumn
Language: Estonian
Tasks: teaching practical sessions once a week, updating teaching materials (labs and homework)
Required skills: basic knowledge of Python, AI, NLP, courage to teach. Previous experience with the course is a bonus.
Other important information: several spots available - think how many groups you are ready to teach the same thing to.
Operating Systems (LTAT.06.001)
Contact: Alo Peets, alo.peets@ut.ee
Semester: Autumn
Required languages: Estonian
Tasks: preparing, teachings and grading labs
Required skills: Good communicator, high knowledge about the workings of a computer and operating system
Computer Security (LTAT.06.002)
Contact: Alo Peets, alo.peets@ut.ee
Semester: Spring
Required languages: Estonian
Tasks: preparing, teachings and grading labs
Required skills: Good communicator, high knowledge about the workings of a computer and operating system
Business Data Analytics (MTAT.03.319)
Contact: Ahmed Sabir, ahmed.sabir@ut.ee
Semester: Autumn
Required languages: English
Tasks: assist with teaching the lab section
Required skills: Python and basic machine learning algorithms (e.g., logistic regression and K-means)
Other important information: The lab section is online, and all materials have already been prepared
Machine Learning MTAT.03.227
Contact: Anna Aljanaki, anna.aljanaki@ut.ee
Semester: Autumn
Language: Estonian
Tasks: teaching practical sessions once in two weeks
Required skills: knowledge of Python and basic machine learning techniques (K-means, PCA, SVM, multi-layer perceptron, scikit-learn), ability to explain techniques in a simple way
Other important information: this is a course taught to master students on the conversion master curriculum. They have a practice session once in two weeks (7 sessions total). Practical materials are available. Preference for someone who is not too far advanced in these topics, as you may be better positioned to explain things simply and recall what was challenging when first learning them.