Students in the Computer Science program are required to fulfill coursework in an Application Area. An application area consists of three courses (9 hours) in a single area offered by another department. This coursework must also form a coherent set of courses. If a defined minor exists in the discipline of the application area, then a good set of suggested courses for the application area would be a subset of the minor. Students should consult their advisor to ensure their application area courses will meet this graduation requirement. The clusters below also list some example application areas that are not traditional disciplinary minors.
Major Electives (aka 500-level electives)
Computer Science majors are also required to take 9 credit hours of CSCE 500-level (or above) courses, or CSCE 317.
A computing cluster is a set of classes that prepare the student for work in a particular domain. Clusters are not part of the degree requirements, and they do not receive any special mention in the student's diploma or transcript. Clusters are simply suggestions for students who have an interest in some application domain and are wondering which classes to take. The clusters are put together so that they also satisfy a student's application area requirement and part (sometimes all) of the students' CSCE electives requirement. For example, a student that wants to work in the video game industry should take the classes in the computer games cluster, which will also fulfill his application area requirement and part of his CSCE electives requirement.
Course clusters contain at least three advanced application area courses offered by at most two other departments and at least two advanced CSCE courses taken as major electives. It may be necessary to take additional courses as prerequisites to the application area courses if they are not already required in the program of study. The requirements specified are minimum requirements, and students are strongly encouraged to take additional courses. Some cluster options may increase the total number of hours required for the degree.
The department has defined computing course clusters in several areas and may identify additional areas in the future.
Advances in Bioinformatics and Computational Biology are making critical contributions to disease detection, drug design, agriculture and environmental sciences through the
development of computational methods including simulation and modeling, database design, high-performance computing, pattern recognition methods, search algorithms,
statistical methods and visualization techniques.
Bioinformatics and Computational Biology is increasingly recognized as a distinctive scientific discipline combining aspects of computer science, statistics, mathematics, and
biology, as well as related areas such as biochemistry and physics. The Department of Computer Science and Engineering addresses the growing national and regional demand
for trained multidisciplinary scientists.
- CSCE courses: CSCE 555, one course selected from CSCE 565, 567, 569, 582
- Prerequisite courses: BIOL 101, 102, CHEM 111, 112
- Recommended Application area courses: BIOL 302, two additional courses selected from BIOL 301, 303, CHEM 333.
Computer Game Design and Programming Cluster
The computer game industry is booming and its revenue is expected to double from 2005's $32 billion to $65 billion in 2011. As a result, thousands of jobs will be created every year in the US alone. To meet this demand, the Department of Computer Science and Engineering offers a focus in computer game design and programming. As a first step, we offered an elective course in Spring 2007, with more than 30 students enrolled. In this class, students formed six groups to design, develop and test fully functional 3D games using commercial or open source game engines. We will continue to extend our education regarding computer games so that students will learn enough skills to pursue careers related to computer games.
We have a strong group of faculty who are experts in computer vision, graphics, multi-media and algorithm design, and we will offer several courses related to game design and implementation. The computer game focus will also encourage students to take several key courses from other departments, including media arts and mathematics. The recommended courses are:
- CSCE courses: CSCE 552, two courses selected from CSCE 520, 565, CSCE 572, 580 (6 hours)
- Suggested Application area courses: Three courses selected from MART 110, 210, 380, 581D, 371, 571C,,MATH 527, 576 (9 hours)
Data Science Cluster
A data scientist brings together knowledge of programming, artificial intelligence, databases, math and statistics, along with domain knowledge, to analyze and extract actionable information from large databases. Data science and Big Data analytics are growing in demand. The New York Times reports that "There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data." If you are interested in becoming a Data Scientist we recommend:
- CSCE 520: Databases
- CSCE 580: Artificial Intelligence
- CSCE 587: Big Data Analytics.
- CSCE 582: Bayesian Networks and Decision Graphs
- CSCE 567: Visualization Tools
- Also, perhaps: CSCE 578: Text Processing
Recommended Application Area courses:
One of the following two sequences of classes.
- STAT 530 Applied Multivariate Statistics (prereq STAT 509), STAT 511 Probability (prereq MATH 241), STAT 535 Bayesian Data Analysis (prereq CSCE 582 or, STAT 511 and STAT 515)
- STAT 511 Probability (prereq MATH 241), STAT 512 Mathematical Statistics (prereq STAT 511), STAT 513 Theory of Statistical Inference (prereq STAT 512)
Computer Forensics Cluster
One of the side effects of the pervasive spread of computing is the increased use of computer and information technology in support of criminal activity, such as identity theft and computer-based scams. Computer forensics addresses the problems associated with the detection, investigation, and prosecution of computer-based crimes. Work in computer forensics requires not only knowledge of computer technology but also knowledge of laws and legal procedures.
We have a strong group of faculty who are experts in information assurance and computer security. We offer a strong foundation for work in this area, including two upper-level courses in computer security and forensics. Supporting courses are from Criminal Justice, Law, and Journalism. The recommended courses are:
- CSCE courses: CSCE 517, 522
- Recommended Application area courses: Three courses selected from CRJU 313, 314, 341, LAWS 525, 526, 547, JOUR 303, 504
Geographic Information Systems (GIS) Cluster
- CSCE courses: CSCE 520, two courses selected from CSCE 564, 565, 567
- Recommended Application area courses: Three courses selected from GEOG 341, 345, 363, 541, 551, 562, 563, 564
- CSCE courses: Two courses selected from CSCE 520, 531, 587, 580
- Prerequisite or required courses: LING 300 OR LING 301
- Recommended Application area courses: Three courses selected from LING 340, 421, 440, 565, 567
New Media Cluster
- CSCE courses: Two courses selected from CSCE 520, 552, 564, 565, 567
- Prerequisite course: MART 110
- Recommended Application area courses: MART 210, 371 or 380
Risk and Insurance Cluster
Insurance is used to manage many of the risks faced by individuals and companies by transferring the risk to an insurance company; the company accepts the risk in exchange for a premium. Insurance companies need to keep track of premiums and payments. They also need to understand and model the risks involved in their market segment.
We have faculty members who specialize in risk analysis, information systems, and computer security and teach courses related to these areas. The Moore School of Business
has several faculty members who specialize in insurance from the business perspective. Modeling risks also involves the use of statistics and mathematical models.
- CSCE courses: CSCE 520, 522
- Prerequisite courses: ACCT 222, ECON 224 (ECON 224 may be used to satisfy the Social Science General Education Requirement)
- Recommended Application area courses: FINA 363, two courses selected from FINA 341, 442, 443, 444, 445
Scientific Computing Cluster
Students with good mathematical skills should consider a track in scientific computing, also called computational science. This is a blend of computer science, applied mathematics, and discipline science such as physics, chemistry, or perhaps geology. Jobs for experts in scientific computing exist with the Department of Energy laboratories (Savannah River, Oak Ridge, Los Alamos, etc.) or the aerospace, automotive, or petroleum industries, to name three examples.
Most scientific computing problems are large-scale problems, and parallel computing is necessary in order to have the programs finish in a timely way. Most problems also generate large amounts of data, so visualization is used to view the data to gain insight rather than just have numbers as output.
We have faculty members who specialize in algorithms and architectures for scientific computing in a variety of fields and regularly teach courses in these areas. Exceptionally well prepared students should consider a double major in Computer Science and in Mathematics. This can be done with a careful choice of coursework with no additional credit hours required beyond that for the two majors.
- CSCE courses: One course from CSCE 564, 565, 567, 569
- Prerequisite courses: MATH 141, 142
- Recommended Application area courses: MATH 242, 300, and one course from MATH 520, 546, 554, or 574.
Aerospace Engineering Cluster
Students interested in working in the aerospace industry will benefit from this cluster. We also recommend the Aerospace Engineering Minor for those who wish to learn even more about Aerospace Engineering.
- CSCE courses: Three CSCE 500-level electives that cover topics of either graphics, simulation, or algorithms.
- Recommended Application area courses: EMCH 577: Aerospace Structures I, EMCH 578: Introduction to Aerodynamics, and then either EMCH 508: Finite Element Analysis in Mechanical Engineering or EMCH 585: Introduction to Composite Materials.
Students interested in the physical -- as well as cognitive or algorithmic -- aspects of robots will benefit from this cluster.