Feedback from students 2023

[shappiron]

Please, state (maximum) three things that you liked about the course

• I liked clear structure with great presentations, interesting homeworks, very friendly atmosphere practical, TAs care and explain good, good organizations
• No exams, high weight of ML competition and team project The content is based on modern up-to-date science Usage of Jupyter Notebooks and interactivity they provide
• The dedication of the course team, it is inspiring.
• The course was diverse in its approaches and presented holistic picture of the aging science. The h/w were incredibly interesting. Professor Khrameeva and TAs were super supportive.
• I liked that course is very practical, enjoyed machine learning part and work on projects
• 1. Practical tasks 2) Combining biology and programming, I get a lot of useful things 3) Kind and helpful professor and TAs
• The overall course structure, that included different aspects of CBA and the overview of cutting-edge research in the field Coursebook with all the materials A lecture on industry by A.Strygin as an invited lecturer Final projects on different topics - a lot of practical work - interesting projects in the end, possibility to discuss them with your classmates - invited lecturers on current state of ageing industry
• The first course on ageing in Skoltech, great review of most important data analysis concepts, useful homework

Please, suggest concretely how this course could be improved

• More lectures and homework (a lot of time is dedicated for project)
• Maybe more topics and more deeply go to the SOTA methods (in ML and DL)
• I suggest adding more information and details about biology, because I did not gain much new knowledge. Also some students were unfamiliar with the basics of ML. I think it was needed to organize an additional lecture on ML for them.
• Better organization of contest part (e.g. via YandexContest, to avoid problems with Kaggle verification).
• This course is the best.
• I think, the content is too dofficult for people, who has never deal with Data Science. I think, breif introduction in the models, trees and other DS terms would be great, because I'm from LS and I have learned all this things by myself and with help of other guys on the course. It was really hard, but I think, my decision to get this course was right, it was really interesting, thanks a lot!
• We had a lot of technical troubles with installation in Hw2 on Diff expression analysis Especially
• on Windows and with R libraries It would be helpful to fix it somehow - perhaps add something on epigenetics based ageing clock (and corresponding practical part)
• The biology of ageing was presented too overwhelmingly, I'd like to see maybe fewer points but more elaborated fundamental concepts. And Binder is still not the best option to run code in class, it's better to go for the git cloning option straight ahead, or at least for the Google Colab =)

My summary

• Need to add more course materials, topics, and practical tasks.
• Add additional lecture on aging biology
• Need to add a brief introduction to ML/DS approaches
• Add Google Colab button (as we planned initially)