200
Prerequisite: CS 100 or the equivalent introduction computer science.
This course introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Students will learn to use a combination of tools and techniques, including spreadsheets, SQL and Python to work on real-world data sets using a combination of procedural and basic machine learning algorithms. They will also learn to ask good, exploratory questions and develop metrics to come up with a well thought-out analysis.
Credits
3.0
Offered
Spring Semester
Prerequisites: Level III placement on the Basic Math Skills inventory or MATH 120 (may be taken concurrently). General programming techniques for students who have had some previous experience with computer programming. Topics include: algorithmic problem solving, top-down design, object-oriented programming and design, and an introduction to abstract data types. Instruction in a high-level programming language.
Credits
4.0
Offered
Both Semesters
Prerequisites: CS 201 and MATH 207 (or concurrent enrollment) or permission of the instructor. An introduction to the structuring and manipulation of information with implementation in the high-level programming language Java. Topics include: linked lists, sets, stacks, queues and trees; basic manipulation techniques including sort/merge and search algorithms; an introduction to algorithm efficiency analysis.
Credits
4.0
Offered
Both Semesters
Prerequisite: CS 202 and MATH 207 Intensive introduction to object-oriented programming and advanced data structures. Topics include heaps, priority queues, hash tables, B+, B* trees and graphs. Emphasizing advantages and disadvantages of design and implementation choices, and the way these choices affect software quality. Instruction will be in the C++ programming language.
Credits
3.0
Offered
Both Semesters
Prerequisites: CS 201 and MATH 207 or permission of the instructor. A comprehensive introduction to the general organization, architecture and functional characteristics of computer systems. Topics include machine level representation of data, assembly level machine organization, memory systems organization and architecture, alternative architectures and device interfaces.
Credits
3.0
Offered
Fall Semester
This course is a general topics course in computer science allowing faculty and students to study particular special interests.
Credits
1.0 - 3.0
Offered
As Needed