ECE-661

COMP ENG ML & DEEP NEURAL NETS

Offered Fall 2026
ELEC&CMP · Taught by Li, Hai · Last offered Fall 2025
Term
Instructor

Overview

Feedback is mostly positive. The strongest signal is that students generally rate the course well. Difficulty runs on the high side even without a single dominant complaint theme. Best for students who can handle a demanding pace without needing constant hand-holding.

DepartmentELEC&CMP
Terms offeredFall, Spring
Typical enrollment57–101
Semesters of data5
7.2
Hrs / week
207
Responses
473
Enrollment
44%
Response Rate

Evaluation Scores

Overall quality
Teaching, content, and experience combined.
4.1
12345
Intellectually stimulating
Challenges students to think deeply.
4.3
12345
Instructor effectiveness
Explains concepts and facilitates learning.
4.1
12345
Difficulty
Higher means harder.
3.8
12345

Feedback Analysis

Feedback Analysishigh
Analysis based on student evaluations
Based on 224 comments across 6 sections

Feedback is mostly positive. The strongest signal is that students generally rate the course well. Difficulty runs on the high side even without a single dominant complaint theme. Best for students who can handle a demanding pace without needing constant hand-holding.

Student Reports
How hard is the A?
A difficulty is mixed
The reports split here. Some comments frame grading as fair and reachable, while others describe stricter standards or more work than expected to land top grades.
Homework Load
Moderate homework load
Homework load looks moderate. The recurring signal is steady weekly work, but not a course that turns every assignment into a grind.
Lecture Load
Lighter lecture burden
Student comments describe this as more discussion-, seminar-, or workshop-driven than lecture-dependent. The lecture burden itself does not sound like the main source of friction.
Strengths
Instructor ratings are strong even when the comments do not cluster around one obvious positive theme.
Tradeoffs
Difficulty runs high even when comments do not settle on one dominant complaint.
Best fit for
Best for students who can handle a demanding pace without needing constant hand-holding.

Student Responses

I learned a lot of new things about adversarial attacks on neural networks. How weight sharing works in deep neural networks. How a neural architecture search works for AutoML.
Fall 2024 · Chen, Yiran
we got insight into the ideas and practice of deep learning neural network. Difference strcutures in CNN such as Vnet and AlexNet. We also overed adversarial attack where we used PGD and FSGD algorithms to create attacks to train the clean dataset.
Fall 2024 · Chen, Yiran
I developed a much better understanding of many deep learning concepts, as well as the practical situation for many of these concepts, and most importantly, HOW to actually implement them.
Fall 2024 · Chen, Yiran
Through hands-on projects, I learned to implement machine learning algorithms and deep neural networks using frameworks like TensorFlow and PyTorch. This included preprocessing datasets, constructing models, training them on real-world data, and fine-tuning hyperparameters to improve performance.
Fall 2024 · Chen, Yiran
This course taught me to not be scared of deep learning or neural networks and actually understand the working behind them
Fall 2024 · Chen, Yiran

Rating History

Rating history
Error bars show \u00B11 std dev
TermInstructorOverallDifficultyHrs/wkEnrolled
Fall 2025Li, Hai 3.1Rate My ProfessorsQuality3.1Difficulty2.8Would retake45%Based on 11 ratingsClick to view on RMP →7.1172
Spring 2025Li, Hai 3.1Rate My ProfessorsQuality3.1Difficulty2.8Would retake45%Based on 11 ratingsClick to view on RMP →4.23.87.675
Fall 2024Chen, Yiran 3.6Rate My ProfessorsQuality3.6Difficulty3.4Would retake67%Based on 12 ratingsClick to view on RMP →4.33.97.268
Spring 2024Chen, Yiran 3.6Rate My ProfessorsQuality3.6Difficulty3.4Would retake67%Based on 12 ratingsClick to view on RMP →7.057
Fall 2023Li, Hai 3.1Rate My ProfessorsQuality3.1Difficulty2.8Would retake45%Based on 11 ratingsClick to view on RMP →4.03.8101

Instructor

Li, HaiELEC&CMP
Also teaches
ECE-550D FUND COMP SYSTEM & ENGINEERING