Computer Science 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, you’ll take classes that 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.
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 one of the leaders in the computer science education field.
- Computer Scientist
- Network support specialist
- Computer science teacher
- Information security analyst
- Software developer
- Web developer
It's Different Here
$103,550 starting salary
for computer science graduates.
1 million jobs
More jobs will be available in computing than graduates to fill those jobs by 2026!
Degrees lead to careers
Fredonia students have been hired by big-name companies such as IBM, General Dynamics, Google, Microsoft, Yahoo, and Lockheed-Martin the past three years.
Why Computer Science at Fredonia?
State-of-the-art computer lab gives students access to the most up-to-date computer programming available. The lab is also equipped with several servers that enable students to gain experience as system administrators.
Student-run Computer and Information Sciences and Video Game Clubs; students compete in several student programming contests, such as the Association of Computing Machinery student collegiate competitions and the CCSCNE conference student competitions.
Fredonia graduates have been hired immediately after commencement at high-profile companies like General Dynamics, Raytheon, Google, Lockheed Martin, IBM, and Paychex.
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.