Current instructor
Original student reviews · all captured dates
Mike is a great professor and clearly teaches the subject. The course is mostly graded on projects that you should be able to get 100% on (you can redo as many times as you want before the deadline). The TAs and peer mentors have office hours all the time and are super helpful.Rate My Professors ↗
Mike was genuinly fun to learn from not text heavy made light jokes and was actually someone whose class i enjoyedRate My Professors ↗
One of the best professors I have ever had! Attend lectures and solve the projects by yourself, and you'll get an A.Rate My Professors ↗
His overall does not reflect him well anymore. He used to be not a great professor but he had a heart attack and now he is super relaxed all the time. He gives out extensions super easily and he seems to really care about teaching. He is incredibly smart and knowledgeable.Rate My Professors ↗
He was great, played Fortnite lobby music to start class one day, and it was a great beginning.Rate My Professors ↗
His lectures are very helpful in understanding the niche code rules, and the only con really was that when he made a mistake, he would fix it and move on quickly. I did not have to do any extra reading/work outside the class besides the graded assignments. The class in general is very manageable, and I did not come in with code experience.Rate My Professors ↗
Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.
Introduction to Data Science programming using Python with no prior experience required, emphasizing analysis of real datasets and visual communication.
Offering recorded · Spring 2027 · Sources
Past student reviews · Michael Doescher
Michael Doescher taught a project-heavy course with unlimited resubmissions. Students reported workloads exceeding 12 hours weekly, though others found the material manageable despite having no prior coding experience.
historical GPA · grades
Fall 2022–Spring 2026Introductory Data Science Programming I for Research course covering Python, programming basics, web scraping, database queries, and tabular analysis.
Offering recorded · Spring 2027 · Sources
Recent recorded grades — Spring 2025: 3.86 GPA, 96.6% A/AB (n=29 letter grades); Fall 2025: 3.77 GPA, 100.0% A/AB (n=13 letter grades); Spring 2026: 3.92 GPA, 100.0% A/AB (n=6 letter grades). Includes jointly taught sections.
historical GPA · grades
Fall 2022–Spring 2026Distinct courses recorded per term
Explore courses taught by this instructor →| Term | Course | Title |
|---|---|---|
| Spring 2027 | COMPSCI 220 | Data Science Programming I |
| Spring 2027 | COMPSCI 319 | Data Science Programming I for Research |
| Fall 2026 | COMPSCI 220 | Data Science Programming I |
| Fall 2026 | COMPSCI 319 | Data Science Programming I for Research |
Teaching history may be incomplete. Course pages contain course-specific feedback and citations.
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