Professor: Karniadakis Course format: Lecture	Number of respondents: 10 Total Enrollment: 15
Class Composition: Froshs: 0 Sophs: 2 Jrs: 2 Srs: 6 Concs: 0 Non-Concs: 10 Don't Know: 0

Instructor Average: 1.95 Course Average: 1.84

“Introduction to Numerical Analysis” is the answer to all those who have done and now despise doing calculations in linear algebra by hand. Targeted towards students majoring in computer science, this class uses computational methods to solve problems involving matrices rather than taking the traditional paper-and-pencil approach. The prerequisites for this course are knowledge of linear algebra and some experience with programming languages.

Professor Karniadakis received mixed reviews from his students. Some felt that he went through lectures too quickly and did not pause to assess the comprehension level of the class. However, they noted that he did slow down when requested by students, and responded well to any question asked. Others pointed out that he was extremely flexible with homework deadlines, and there was even some desire on the part of the class for him to enforce them more rigidly than he did.

Opinions toward the text used for the course were divided as well. Some felt that the book did a good job of conveying and reinforcing the concepts taught in class, whereas others found it confusing and hard to understand. There was a homework assignment each week in addition to a single take-home midterm and an in-class final. Finally, class members were expected to complete a project as well. All in all, this workload met some reviewer’s expectations and failed others.

In general, people reported spending around four to eight hours per week on the course outside of class. Most students enrolled in this class did not find the material thrilling, but considered it to be a useful skill to acquire as a computer science major. If the material sounds interesting to you, give “Introduction to Numerical Analysis” a shot.

View AM/0117 in the Brown Online Course Announcement.