In the course, students will have to write some study/learning logs, after lectures/hands-on sessions. This document provides a simple guideline about study logs for CS-E4660.
In CS-E4660, we interpret: a study (learning) log is used to analyze what has been learned and to discuss relevant issues and thoughts identified through the study
Therefore, we expect you to analyze important aspects and raise critical points that you think we should discuss and tackle, based on the study materials in connection with your individual interests/works. Writing a simple activities or listing topics you have learned are not a good indicator for this course.
| Study logs | Fail | Pass |
|---|---|---|
| Papers/topics studied | List papers/topics you learn/read | Raise the most important, relevant topics you think and why |
| Knowledge learned | Just tell "I have learned a lot" | Tell "I have learned a lot" because the knowledge you learned was missing/not covered from which perspectives |
| Tools studied | Tools A, B and C can be used for big data/ML orchestration | "I do not prefer any tool among Tools A,B and C, because I do not know them so I need time to investigate them" or "I think Tool A is much better than Tool B for ML because it is easy to use and supports many libraries" |
| Decision | Just say "I plan to study topic A" | Tell the reason "I want to spend more time to study Topic A because ..." |
A good way to write study logs is to give the reasons based on your understanding, expectation and decision, e.g.,
- Among topics A,B and C, topic A is the most interesting one in my opinion because it helps ...
- I think that topic A needs to be discussed more detail w.r.t. aspect XYZ. The reason is ...
- I think that technique T1 can be applied into domain D1 to solve problem P1. The reason is
- I would like to apply technique T1 for my big data pipeline because ...
- I found another tool/paper which was not covered by the course but I think it is interesting because ...