Data Science & Engineering
Introduction to Data Science using Python for data analysis and prediction.
Summary
Historical reviews of Grigoris Chrysos: Students report that homework assignments take hours and are often impossible, requiring serious independent study. Exams are described as incredibly tough and unrelated to lecture material.
Grade history
↗letter grades
All recorded terms · compare terms & instructors
Prerequisites
Course mapProfessors
Fall 2026No instructors recorded for this selection.
Historical instructors & teaching patterns
Historical reviews of Grigoris Chrysos: Grigoris Chrysos taught ECE 204 in Spring 2024. Reviewers report that he treated the introductory course as advanced, assigning out-of-scope homework and exams featuring difficult LeetCode-style problems. Students criticized his poor empathy, belittling Piazza responses, and refusal to adjust expectations for novices.
GRIGORIS CHRYSOS is recorded teaching in Spring 2024. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Historical reviews of Grigoris Chrysos: Reviewers describe Grigoris Chrysos’s ECE 204 as unexpectedly difficult, with exams and homework containing out-of-scope material and LeetCode-style problems. Many students recommend avoiding the course or having prior Python experience.
Recent recorded grades — Fall 2024: 3.70 GPA, 90.1% A/AB (n=71 letter grades); Spring 2025: 3.60 GPA, 91.5% A/AB (n=82 letter grades); Fall 2025: 3.65 GPA, 85.7% A/AB (n=70 letter grades).
difficulty & workload
Historical reviews of Grigoris Chrysos: Students report that homework assignments take hours and are often impossible, requiring serious independent study. Exams are described as incredibly tough and unrelated to lecture material.
Historical reviews of Grigoris Chrysos: Reviewers criticize Chrysos for being rude on Piazza and ignoring student concerns about the course difficulty. One student found the data science lessons interesting, but others found the experience frustrating.
Topics
Skills
Grades
Latest available · Fall 2025— not enough history to project Fall 2026.
Grade distribution · % of letter grades
Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Where this course fits relative to
Latest available grades · Fall 2025 · all course levels
GPA
Higher than % of other courses in this group.
Course GPAs · red marks this course’s range
letter grades
More recorded grades than % of other courses in this group.
Typical course in this group: letter grades.
About this comparison
1320 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.
Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
No offering records for the selected term.
Raw records
[]
Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesModel outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "fddaf3237854089af308b7fea1ffe55eb0a3dce02db0f1cc413ae302af488aa1",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}