Homework 10: Course feedback¶
This homework is to be done individually, not in groups. Your responses are not to be put in your GitHub account so you can speak candidly without the influence of your teammates. You do not need to use a Jupyter notebook to do the problem. Instead, you should submit your responses either as a PDF or just as text in an email. Do not submit a MS Word document or a Jupyter notebook. Please email your responses to all of the following email addresses.
bois at caltech dot edu palmhjell at caltech dot edu candrews at caltech dot edu sbeeler at caltech.edu jciemnie at caltech dot edu muir at caltech dot edu saladi at caltech dot edu
A total of 30 points will be awarded for thoughtful responses for this homework. I am not expecting a paragraph for each question, but if you have detailed comments on something you have a strong or insightful opinion about, I would like to hear them.
Problem 10.1: Topical coverage¶
a) Before discussing topics of this course, are there topics you would like to have discussed next term in BE/Bi 103 b?
b) Are there topics you would like covered that were not?
c) Were there topics you think we spent too much time on?
d) Which topics did you find most interesting?
e) Which did you find most pertinent?
f) Where there any common misconceptions that persisted throughout the course for you? What topics (if any) did you find particularly hard to understand and apply?
Problem 10.2: Data sets and exercises¶
a) What was your favorite homework problem or data set? Which problem would you remove? Why?
b) Did you like that we kept revisiting data sets throughout the term? (We can always do less of that, but we can do even more of that. E.g., we could do image processing on the original Singer, et al., mRNA FISH images.)
Problem 10.3: Course structure¶
a) Where did the majority of your learning take place? (Example answers include: Reading the lessons, doing the lesson exercises, completing the homeworks, interacting with TAs during the Monday sessions, interacting with TAs during office hours, during JB’s lectures, during JB’s office hours, talking with teammates, etc.)
b) How would the class have been different for you if the work weren’t done in teams?
c) Do you have any suggestions for improvement of the Monday sessions?
d) Did you like using GitHub as a platform for collaboration and submission?
e) What advice would you give to future students about using GitHub? Were there any common problems you frequently encountered?
f) Did you attend any recitation sessions? Did you find them useful? Do you have general suggestions for that?
g) Did you find the homework help sessions useful? Do you have general suggestions for that?
h) Do you have any comments on the lecture style or material?
i) Do you have any suggestions for improving the course website and/or dissemination of material?
j) What are your opinions on Ed as a way to discuss course material and get help?
Problem 10.4: Your future¶
a) What will you be able to do with your data that you weren’t able to before?
b) Has this class changed the way you read scientific papers? Has it changed your opinion on any papers you’ve read previously?
c) Which of the following principles do you think you will apply in your work going forward?
Other visualization techniques we learned (please specify)
Generative modeling and MLE
Automated image processing
d) Which of the following software tools do you think you will use in your work going forward?
Python-based tools in general (NumPy, SciPy, etc.)
bokeh_catplot(soon to be superceded when HoloViews adds functionality)
bebi103package (utilites we used in teh course)
Griffin Chure’s workflow
Griffin Chure’s website template
e) Do you expect to coordinate with CaltechDATA (as discussed in Tom Morrell’s guest lecture)?
f) Will you share what you have learned with your labmates/classmates?
g) Will you share what you have learned with your PI?
Problem 10.5: Miscellany¶
Please include any comments you have that I have not asked about.