COMPSCI 639 is an undergraduate elective covering selected topics in computing, with specific content determined by the instructor for each offering.
Reviewers describe the homework as interesting and hands-on, while one reviewer characterizes the overall class difficulty as hard.
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Swamit Tannu effectively explains quantum computing basics and industry context, with reviewers noting his helpfulness and accessibility during office hours. He supports students in understanding high-level research concepts. While some find the course difficult, others rate it as manageable, though all praise the engaging material.
Recent recorded grades — Spring 2025: 3.71 GPA, 88.1% A/AB (n=42 letter grades); Spring 2026: 3.69 GPA, 85.7% A/AB (n=49 letter grades). Includes jointly taught sections.
Historical reviews for Bilge Mutlu highlight rewarding projects and student care, though early course structure was criticized. Josiah Hanna is praised for clear lectures, approachable teaching, and well-organized content. These past experiences suggest a positive trajectory for the course under different instructors.
BARTON MILLER is recorded teaching in Spring 2019, Spring 2020. Recorded history may be incomplete and does not establish a future schedule.
BILGE MUTLU is recorded teaching in Spring 2018, Fall 2018, Spring 2019, Fall 2019, Fall 2020, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
EFTYCHIOS SIFAKIS is recorded teaching in Spring 2020, Spring 2022, Spring 2023, Spring 2024. Recorded history may be incomplete and does not establish a future schedule.
JOSIAH HANNA is recorded teaching in Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
SWAMIT TANNU is recorded teaching in Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
YONG JAE LEE is recorded teaching in Spring 2023, Spring 2024, Spring 2025. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 002 | Classroom Instruction | 83 / 132 | 0 |
| LEC 003 | Classroom Instruction | 139 / 150 | 0 |
| LEC 004 | Classroom Instruction | 40 / 50 | 0 |
| LEC 006 | Classroom Instruction | 68 / 75 | 10 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Swamit Tannu teaches a new course on quantum computing basics that reviewers find interesting and helpful, though one notes the class is hard.
Recent recorded grades — Spring 2025: 3.57 GPA, 77.3% A/AB (n=348 letter grades); Fall 2025: 3.62 GPA, 85.0% A/AB (n=80 letter grades); Spring 2026: 3.70 GPA, 84.1% A/AB (n=546 letter grades).
Reviewers describe the homework as interesting and hands-on, while one reviewer characterizes the overall class difficulty as hard.
Students appreciate Tannu's accessibility during office hours and his ability to explain high-level industry concepts and research contexts.
– average GPA
Approximate 80% prediction interval
The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.
The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.
6 earlier forecasts · 0.16 GPA average error.
Through Fall 2026
Latest available grades · Spring 2026 · 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.
1283 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.
Descriptions, prerequisites, and recorded course offerings.
Observations at scan time; dates do not imply when a catalog change took effect.
Undergraduate Elective Topics in Computing
Recorded 2026-09-07Sys Arch for Quantum Computers
Recorded 2026-09-07Intelligent Robots
Recorded 2026-09-07AI-Assisted Software Dev
Recorded 2026-09-07Intro Reinforcement Learning
Recorded 2026-09-07Data Mgmt for Data Science
Recorded 2026-09-07[
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"title": "Undergraduate Elective Topics in Computing",
"credits_min": 3,
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},
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"title": "Sys Arch for Quantum Computers",
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"title": "Intelligent Robots",
"credits_min": 3,
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},
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"title": "AI-Assisted Software Dev",
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"title": "Intro Reinforcement Learning",
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},
{
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"offering_id": "1272:266:024923.4",
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"title": "Data Mgmt for Data Science",
"credits_min": 3,
"credits_max": 4,
"typically_offered": "Occasionally"
}
]Original comments behind the course and instructor summaries.
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded model configuration, reasoning, and tool conversations.
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "76d8b09f5bb888d5d3e082db6d4f12e8fdb56e5afdde6146cbb077dbdc4c297e",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}