Course Syllabus

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This course studies the fundamental ideas for efficiently analyzing large amounts of data, such as DNA sequence databases and geographic information. These fundamental ideas come in two kinds: algorithms and data structures. Algorithms are instructions for solving problems and data structures are strategies for organizing information on computers. Efficient algorithms require appropriate data structures, and vice versa, so the study of algorithms and data structures is tightly linked. In this course we learn about the algorithms and data structures that form the building blocks for most of Today's large-scale computer systems. We apply these ideas to solve challenging problems in bioinformatics and geographic information systems. Warning: a possible side-effect of taking this course is doing better on job interview questions.

Instructor

Jeremy Siek, Office hours: Mondays 2-3pm, Fridays 2-3pm, and by appointment. Office: LH 230D.

Assistant Instructors

Each AI is responsible for grading for half of the students in their lab.

To find out which AI is responsible for you, consult this file. If your name is not in that file, please send email to Jeremy.

Lecture

4:00 PM - 5:15 PM, Monday and Wednesday, Optometry Building Room 111

Textbook (required)

Data Structures & Algorithm Analysis in Java (Third Edition, version 3.2) by Clifford A. Shaffer.

Course Schedule

 For the course schedule, follow this link.

Discussion

We will use Piazza for out-of-class course-related discussions. Participating in the Piazza discussions is part of your participation grade.

Late Assignment Policy

You may turn-in assignments (labs, textbook exercises, projects) up to 1 week late and they will still be graded, but with a 10% deduction from your assignment grade.

Resources

 

Course Summary:

Date Details Due