Introduces students to the principal activities involved in developing high-quality software systems. Topics include: requirements analysis, formal specification methods, process definition, software design, and risk management.

Not available at this time

This course offers an introduction to working with Unix, and it is intended to help students work with tools commonly used in CS courses. The class is comprised of both discussion and hands-on exercises in the EdLab. Topics covered include working with the command line, installing and maintaining the OS and software packages, version control systems, compiling programs, and more. No previous experience with Unix is required. This course is for CS minors and majors only, but it does not count towards either degree.

Large-scale software systems like Google - deployed over a world-wide network of hundreds of thousands of computers - have become a part of our lives. These are systems success stories - they are reliable, available ("up" nearly all the time), handle an unbelievable amount of load from users around the world, yet provide virtually instantaneous results.

The theory seminar is a weekly meeting in which topics of interest in the theory of computation - broadly construed - are presented. This is sometimes new research by visitors or local people. It is sometimes work in progress, and it is sometimes recent material of others that some of us present in order to learn and share. This is a one-credit seminar which may be taken repeatedly for credit. May be repeated for credit up to six times.

Introduces students to the principal activities involved in developing high-quality software systems. Topics include: requirements analysis, formal specification methods, process definition, software design, and risk management.

An introduction to computer programming with multimedia applications. Students will create Python programs to process image, video, and audio data. No prior programming experience expected. Not open to CMPSCI majors.

This course provides an overview of the important issues in information retrieval, and how those issues affect the design and implementation of search engines. The course emphasizes the technology used in Web search engines, and the information retrieval theories and concepts that underlie all search applications. Mathematical experience (as provided by CMPSCI 240) is required. You should also be able to program in Java (or some other closely related language).

This course examines the structure of modern computer systems. We explore hardware and technology trends that have led to current machine organizations, then consider specific features and their impact on software and performance. These may include superscalar issue, caches, pipelines, branch prediction, and parallelism. Midterm and final exams, individual projects, homework, in-class exercises. Prerequisites: CMPSCI 535 or equivalent.

Mathematical methods for dealing with uncertainty. Basic counting problems. Discrete probablitlity, expected value and variance. Random number generators and Monte Carlo simulation. Bayesian reasoning, naive Bayes classifiers. Markov processes. Programming projects.