Welcome to CSE 417 (Autumn
2025)
Official Course Title: Algorithms and
Computational Complexity
Primary Instructors: Nathan Brunelle and Glenn
Sun
Course Goals
CSE 417 is an introduction to algorithms. By the end of this
course, you will be able to:
- Discuss how and why certain foundational algorithms work.
- Design algorithms for new problems using a variety of
algorithm-design paradigms.
- Mathematically prove that your algorithm produces the correct
answer.
- Model word problems computationally and consider the
implications of modeling decisions in the real world.
Eligibility
You should take this course only if
- You have credit for CSE 373 or equivalent
- You are NOT a CSE major
| Platform |
Purpose |
| This website |
Main location of
public course content: syllabus, schedule,
readings, homework descriptions, etc. |
| Canvas |
Main location of
private course content: homework submissions,
lecture recordings, sample solutions, etc. |
| Ed Discussion Board |
Questions and discussion with staff
and other students |
| Gradescope |
Used for submitting programming
assignments only |
Tips for success in this
course
In this course, you will learn some particular noteworthy and
widely-used algorithms, as well as learn and apply techniques to
develop your own algorithms to solve new problems. This will be at
times uncomfortable and frustrating, so we have a few suggestions
for how to navigate this:
- If something is not clear, ask. In lecture,
other people probably have the same question. On homework and
exams, our intent is never to ask trick questions, so ask on Ed
for clarification.
- Reason carefully and precisely. Although we
won’t purposefully mislead you, we may ask questions that are
designed to expose flawed intuition or a common misconception.
Reason step-by-step, and avoid
intuitive
statements that
are actually logical leaps.
- Use techniques from lecture in your homework.
Homework problems will always use techniques recently covered in
lecture. Also note that most homework will be about reinforcing
techniques from lecture, not specific algorithms
or examples.