Computer Science Degree Program at Fredonia
Solve problems with Computer Science
Computer Scientists refine our understanding of technology and its applications. Accelerate your career in the vast and growing field of computer science.
- Advance your skills with a computer science degree curriculum encouraging formal, abstract, theoretical and practical approaches to the study of computer science.
- Cultivate creative thinking, problem-solving, and research proficiency as you develop specialized expertise.
The Fredonia Difference
Computer Science is one of our most popular programs for a good reason. Graduates have a strong track record of moving into high-paying jobs--or high-profile graduate schools-- immediately after graduation. Whether you’re interested in artificial intelligence (AI), machine learning, digital image processing, robotics, cybersecurity, or the internet of things (IOT), our dedicated faculty and modern facilities are the place to begin.
Career Opportunities for Computer Science Degree
- Computer Scientist
- Network support specialist
- Programmer
- Computer science teacher
- Information security analyst
- Software developer
- Web developer
It's Different Here
Why Computer Science at Fredonia?
Sample Courses
CSIT 441 Analysis and Design of Algorithms
Introduction to design and analysis of algorithms: time and space complexity, verification of correctness; advanced algorithm design strategies: iterative, divide and conquer, greedy method, dynamic programming, branch and bound, etc.; specific examples drawn from sorting, searching, string searching, graph problems, matrices, polynomial arithmetic, cryptography; hard problems and approximation algorithms: Knapsack, bin packing, and graph coloring problems, etc.
CSIT 461 Introduction to AI and Knowledge Engineering
Overview of artificial intelligence tools and techniques; searching methods; applications of AI: game playing, expert systems and knowledge-based systems; components of a knowledge-based system; knowledge acquisition, representation, and formalization; numerical and symbolic processing; information theoretic and decision theoretic algorithms; inference engine; machine learning; reasoning and explanation; basic concepts and major issues of knowledge engineering; current tools and techniques for analysis, design, development of the knowledge based systems; applications in robotics, medical diagnosis, smart decision systems, etc.
CSIT 463 Introduction to Digital Image Processing and Computer Vision
Introduction to digital image and signal processing, computer vision and pattern recognition; image acquisition, registry and display; elementary image processing algorithms: sampling, preprocessing, smoothing, segmentation, and sharpening; transformations; filtering; image coding and restoration; analog and digital images and image processing systems; feature extraction and selection; elementary pattern classification and vision systems; robotics; machine learning.
Program Additional Links
What does a 4-year degree look like?
What are all the required and elective courses offered to obtain this degree?