You're not currently signed in. Sign in »

CS 450 Numerical Analysis

course description time location
Course catalog entry 3:30-4:45pm TR 1404 Siebel Center

Course staff


name email office hours office
Prof. Paul Fischer 11am-12pm Mondays, 10-11am Wednesdays 4320 Siebel Center

Teaching assistants

name email office hours location
Josh Bevan 1:30-3:30pm Tuesdays SC 0207
Erin Carrier 9:30-11:30am Thursdays SC 0207
Lishen He 9:00-11:00am Fridays SC 0207
Shelby Lockhart 2:00-4:00pm Wednesdays SC 0207


Scientific Computing: An Introductory Survey by Michael T. Heath, McGraw-Hill, 2nd edition, 2002

Discussion forum

Video recordings of lectures

Exams, quizzes, and homework

Exams: two midterms and a final exam, both of which will be offered in the Computer-Based Testing Facility (located in room 57 Grainger Library).

You may have one retry for each of the midterm exams (not the final). See the detailed policies below for more information on exam retries.

Quizzes: approximately weekly, to be taken online on this website (see detailed schedule below). Homework: assignments due every two weeks (see detailed schedule below). Homework will involve both written exercises and computer problems. The latter must be done in Python. Projects: students taking the course for 4 credit hours must complete a term project. See detailed schedule below for various due dates. More project details can be found at the bottom of this page.

More detailed policies on exams, quizzes, and homework are given below.

Course Policies

Homework Policies:

Quiz Policies:

Piazza Policies:

Exam Policies:

Exam Retry Policies:

Class schedule

date topic homework quiz project (4-credit only)
Tue Jan 17 Scientific computing
Thu Jan 19 Scientific computing HW1 assigned Quiz 0 due (no credit quiz)
Tue Jan 24 Linear systems Quiz 1 due
Thu Jan 26 Linear systems
Tue Jan 31 Linear systems HW1 due Wed. Feb 1
Thu Feb 2 Linear least squares Quiz 2 due
Tue Feb 7 Linear least squares
Thu Feb 9 Eigenvalue problems Quiz 3 due
Tue Feb 14 Eigenvalue problems HW2 due Wed. Feb 15
Thu Feb 16 Eigenvalue problems
Tue Feb 21 Nonlinear equations
Thu Feb 23 Nonlinear equations Quiz 4 due
Tue Feb 28 Nonlinear equations HW3 due Wed. Mar 1
Thu Mar 2 Optimization Quiz 5 due
Tue Mar 7 Optimization Proposal due
Thu Mar 9 Optimization
Tue Mar 14 Interpolation HW4 due Wed. Mar 15 Quiz 6 due
Thu Mar 16 Interpolation
Tue Mar 21 Spring break
Thu Mar 23 Spring break
Tue Mar 28 Numerical quadrature Quiz 7 due
Thu Mar 30 Numerical quadrature
Tue Apr 4 IVPs for ODEs HW5 due Wed. Apr 5 Quiz 8 due
Thu Apr 6 IVPs for ODEs
Tue Apr 11 IVPs for ODEs Progress report due
Thu Apr 13 BVPs for ODEs Quiz 9 due
Tue Apr 18 BVPs for ODEs HW6 due Fri. Apr 21
Thu Apr 20 PDEs Quiz 10 due
Tue Apr 25 PDEs
Thu Apr 27 PDEs
Tue May 2 PDEs HW7 due Wed. May 3 Quiz 11 due Final report due

Grading Information

Grade Breakdown

HW 30%
Quiz 10%
Midterm 1 15%
Midterm 2 15%
Final 30%

Grade Scale

Academic Grading System in the US

Course Grade Total Score as weighted above
A+ [97,100)
A [93,97)
A- [90,93)
B+ [87,90)
B [83,87)
B- [80,83)
C+ [77,80)
C [73,77)
C- [70,73)
D+ [67,70)
D [63,67)
D- [55,63)
F [ 0,55)

4 Credit Hour Project Details

All students taking the course for 4 credit hours must complete a project. This project is chosen by the student with the consent of the instructor.

To ensure that a given project is appropriate in scope and content, students must submit a brief description of the proposed project for approval before beginning implementation. The instructor may suggest modifications or alternatives, if appropriate. Projects are evaluated for both correctness and creativity. Projects are graded as satisfactory/unsatisfactory and make no contribution to the final grade, only to the hours of credit received.

Progress proposals, reports and final reports will be submitted on Relate (the course website). Additional details regarding expectations for the progress report and the final project report will be given in the individual submission spots. Due dates for each portion are shown in the schedule above.

Possible types of projects include:

If you are unsure about what project to propose or what sort of project is acceptable, feel free to consult the instructor.

Python Resources

Python is the required programming language for completing the homework problems for this course. Listed below are many good resources available for Python, Numpy/Scipy, and Matplotlib.

General Python Help

Numpy/Scipy Help

Matplotlib Help