- Holden Lee
- holee at math dot duke dot edu
- Office Hours Location
- Gross 352
- Office Hours
- Mon. 4:30-5:30pm
Fri. 2-3pm (starting 1/24)
See Piazza for adjustments.
- MW 3:05-4:20 (Physics 227)
- Available here.
- Shortlink: tiny.cc/math361s20.
- Piazza page
- Math 361S
- Uri Ascher & Chen Greif, A First Couse in Numerical Methods
Excerpts from Cleve Moler’s book Numerical Methods in MATLAB (free online).
Announcements regarding distance learning
- The syllabus has been updated with changes in the class format and policies.
- Lecture videos will be recorded and made available on Sakai. You are asked to watch the videos before class time, and are encouraged to ask questions and discuss the lecture on the Piazza page. Class time will be devoted to discussion and to working out examples. We will experiment with the format, but the general plan is to (a) first devote some time to QA on the relevant material, (b) work out practice problems, and (c) show demos involving code.
- All homework is to be submitted on Sakai. I will not check my mailbox.
- Access virtual class meetings and office hours through Sakai using Zoom. To access the meeting, log on to Sakai and click on "Zoom Meetings" on the left, then click "Join" beside the meeting. Feel free to email me to schedule meetings at other times; these will also be conducted using Zoom. (Let me know if you have any issues with using it.)
- Exam II has been postponed to April 13. It will likely be structured as a take-home exam.
- Let me know ASAP about any situation I should be aware of as I plan the remainder of the semester. This includes but is not limited to:
- Not being available at the regular class time (e.g. because of time zone differences)
- Lack of textbook access
- Lack of internet/microphone/webcam
Development of numerical techniques for accurate, efficient
solution of problems in science, engineering, and mathematics through the use of
Linear systems, nonlinear equations, optimization, interpolation, numerical
integration, differential equations, error analysis.
Solid understanding of fundamental concepts from linear
algebra is essential, including linearity, solving linear systems, eigenvalues and
eigenvectors. A course in multi-variable calculus (e.g. Math 212) is also required.
Experience with ordinary differential equations is recommended, but not necessary.
Grades will be assigned based on an assessment of your performance on homework, midterm exams, and a
final project. The components will be weighted (roughly) as follows:
- Weekly homework (30%)
- Two midterm exams (20% each)
- Final project (30%)
- Participation (Up to 10% extra may be given for participation.)
- There is no final exam for this course.
- Homework will be assigned (roughly) weekly and will typically be due the
following Wednesday. Consult the schedule for due dates.
- No late homework will be accepted,
barring exceptional circumstances as per Duke policy.
- Working and studying in groups is encouraged
(you will get much more out of doing homework if you discuss it with others!).
However, you should write your own solutions to each problem in your own words.
- Solutions should be complete arguments; the process by which you arrive at
the solution is far more important than a correct answer. Assertions should be supported by computed data and code when it is needed.
- Homework pages must be stapled together with clearly readable work.
Solutions should be in the same order as in the list of assigned problems.
- Some homework problems will require writing and running code. The official
programming language for this course is Matlab, but you may write your code in Matlab, Python, or Julia.
- Collaboration is encouraged but the code you submit should be your own,
which includes not copy-pasting code from other sources. Avoid looking up
code online because it is difficult to un-see it when writing your own.
Students are expected to follow the Duke Community Standard.
If a student is found responsible for academic dishonesty
through the Office of Student Conduct, the student will receive a
score of zero for that assignment. If a student’s admitted academic
dishonesty is resolved directly through a faculty-student resolution
agreement approved by the Office of Student Conduct, the terms of that
agreement will dictate the grading response to the assignment at issue.