Lectures are not good -- slides are jam packed with content which is hard to read and understand (like incredibly complicated formulas which aren't even necessary to know). On the bright side though the exams are about a 3.75/5 on the easy scale (5/5 being very easy) and HW is very easy -- so a very easy CS elective and paired well with 577Rate My Professors ↗
Current instructor
Blerina Gkotse
What students say
Original student reviews · all captured dates
Quality 3/5Difficulty 2/5
Quality 4/5Difficulty 1/5
Class is insanely easy, only issue is that the grades are curved rather than actually being cutoffs. So even if you have a 99% going into the final, you could still end up with a C or worse.Rate My Professors ↗
Quality 1/5Difficulty 1/5
They should reduce the percentage weight of the assignments. The way this course is structured is unreasonable. Never seen such a disgusting course.Rate My Professors ↗
Quality 4/5Difficulty 3/5
The class was well structured, and the lectures were informative. The professor seemed knowledgeable and was extremely accessible outside the course.Rate My Professors ↗
Quality 4/5Difficulty 2/5
Her lectures and the class as a whole were fairly well-organized. The curve does not work, though, since 70% of the class is homework and nearly everyone has a grade in the upper 90s going into the final. They try to reassure you by saying "a 90 will likely not get a C"... not really what you want to hear.Rate My Professors ↗
Quality 5/5Difficulty 2/5
She does not want to overwhelm students, and I appreciate the course design. Tests are not difficult. I recommend taking CS540 with her.Rate My Professors ↗
Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.
Classes with Blerina Gkotse
COMPSCI 220 introduces data science programming with Python, focusing on analyzing real datasets and visual communication, with no prior experience required.
Offering recorded · Fall 2026
historical GPA · grades
Spring 2022–Spring 2026COMPSCI 319 introduces data science programming in Python, covering basics, web scraping, databases, and visualization for research datasets.
Offering recorded · Fall 2026
historical GPA · grades
Spring 2022–Spring 2026Recorded teaching history
Explore courses taught by this instructor →Browse recorded courses
| Term | Course | Title |
|---|---|---|
| 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.
Instructor identity & provenance
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