
Computer Science Program at Fredonia
If you want to be a programmer, developer, program manager, or problem solver you’ve come to the right place. In Fredonia’s Computer Science program, your classes will explore the theory of computer science while hands-on experiences allow you to practice your craft and create practical applications and help you develop problem solving skills, which are an essential skill for life. Your Computer Science degree from Fredonia will set you on a path with unlimited potential.
The Fredonia Difference
The Computer Science program is one of the most popular programs at Fredonia. There is a well-established track record of students moving into high-paying jobs immediately after graduation, or into high-profile graduate programs across the country. Innovative classes, dedicated faculty, and modern facilities make Fredonia a leader in the computer science education field. Start your path towards a Computer Science degree today!
Career Opportunities for Computer Science
- 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?
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