This accelerated course covers material from the first-year sequence of courses and provides the foundation for all subsequent Computer Science courses. The course stresses problem solving while covering modern software development techniques and introducing essential software tools. Topics include tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, object-oriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of object-oriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary object-oriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Note: Requires department permission for registration.

This course serves as an introduction to computational thinking using a problem-centered approach. Specific topics covered include: expression of algorithms in pseudo code and a programming language; functional and imperative programming techniques; control structures; problem solving using recursion; basic searching and sorting; elementary data structures such as lists, trees, and graphs; and correctness, testing and debugging. Assignments (both in class and for homework) requiring a pseudo code solution and an implementation are an integral part of the course. An end-of-term project is also required.

This course examines current topics in Artificial Intelligence. This is intended to allow faculty to pilot potential new undergraduate offerings. Specific course details (such as prerequisites, course seminar, format, learning outcomes, assessment methods, and resource needs) will be determined by the faculty member(s) who propose a specific seminar course in this area. Specific course instances will be identified as belonging to the Artificial Intelligence cluster, the Computer Graphics and Visualization cluster, the Security cluster, or some combination of these three clusters.

This course allows students to pursue two threads of research in computer science. One thread is the discovery and analysis of previous work in the field. Students will select, read and collectively discuss papers from conferences and journals in CS. A survey paper on a topic of the student's choice will be required. The other thread is an independent project. Students will select a topic, lay out weekly goals, and meet with the instructor weekly. A final report and presentation will be required.

An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments and oral/written summaries of research papers are required.