Bachelor of Science in Computer Science - Data Science Concentration
The Bachelor of Science in Computer Science (BSCS) program is designed to help students who are interested in a career centered on building computer software solutions through programming with algorithmic techniques, to explore a broad range of theoretical and practical knowledge, methods, processes, techniques and skills to effectively design and develop the computer software according to any domain specific requirements.
The curriculum of BSCS offers broad and detailed knowledge on how a computer’s software works, and how to design and develop all levels and all types of computer software. This is different from the curriculum of the Computer Engineering program which is focused on how to design and develop computer hardware. It is also different from the curriculum of the Information Technology program which is focused on how to apply both computer hardware and software to design, develop and support high level end-user-oriented business systems, services or applications.
BSCS Program Outcomes
• Acquire the theory of programming language, and to program in multiple high level programming languages by using suitable programming fundamentals, abstraction modeling, data structures, and algorithms to solve non-trivial problems.
• Examine and apply the in-depth knowledge of computer architecture, operating systems, databases, parallel computing, mobile computing, software engineering, big data analytics, computer networking and computer security when constructing technical solutions.
• Work both individually and as part of a team to develop and deliver quality software and associated requirements analysis, design and testing artifacts.
• Reconcile conflicting project objectives, finding acceptable compromises within the limitations of cost, time, knowledge, existing systems, and organizations.
• Design appropriate solutions in one or more application domains using broad computer science knowledge foundation and software engineering approaches that integrate ethical, social, legal, and economic concerns.
BSCS- Data Science Concentration Outcomes
•Acquire knowledge of new models, methods, technologies, tools, and the context-specific best practice relevant to big data analytics as they emerge.
•Choose and apply appropriate data analytics theories, models, techniques and tools to construct software solutions to cost-effectively extract, store, pre-process, query, analyze and visualize big data based on the business requirements.
Degree Requirements
Courses: General Education
COMS203 | Speech Communications | 4.5 |
ENGL104 | Introductory Written Communication | 4.5 |
ENGL105 | Professional Written Communications | 4.5 |
HIST101 | Modern American History: 1950 to the 21st Century | 4.5 |
MATH111 | College Algebra for Technical Programs | 4.5 |
PHIL101 | Introduction to Ethics | 4.5 |
PSYC102 | Introductory Psychology | 4.5 |
SCI101 | Introduction to the Sciences | 4.5 |
SCI103 | Science and Technology- Laboratory Course | 1.5 |
SCI201 | Environmental Science and Sustainability | 4.5 |
SOCL202 | Social Perspectives on Race, Gender, and Class | 4.5 |
UNIV104 | Academic and Career Success | 4.5 |
| Total Credit Hours: | 51 |
Courses: Core
CE242 | Computer Architecture | 4 |
CS101 | Problem Solving in Computer Science | 4 |
CS118 | Principles of Programming Languages | 4 |
CS119 | Introduction of Programming | 4 |
CS219 | Python Programming | 4 |
CS221 | SQL Programming | 4 |
CS226 | Java Programming | 4 |
CS228 | C++ Programming | 4 |
CS233 | Fundamentals of Data Structures | 4 |
CS253 | Introduction to Database Systems | 4 |
CS267 | Computer Algorithms | 4 |
CS311 | Mobile Programming | 4 |
CS337 | Introduction to Parallel Computing | 4 |
CS341 | Principles of Operating Systems | 4 |
CS349 | Software Engineering | 4 |
CS356 | Foundations of Big Data Analytics | 4 |
CS491 | Computer Science Team Project I | 4 |
CS492 | Computer Science Team Project II | 4 |
CSS150 | Introduction to Computer Security | 4 |
IT204 | Fundamentals of Networking | 4 |
MATH211 | Applications of Discrete Mathematics for Computer Systems and IT | 4 |
MATH311 | Data Driven Statistics for Computer Systems and IT | 4 |
| Total Credit Hours: | 88 |
Courses- Concentration
CS367 | Streaming Data Analytics | 4 |
CS397 | Data Warehousing | 4 |
CS378 | NoSQL Databases | 4 |
CS379 | Machine Learning | 4 |
CS473 | Data Mining | 4 |
CS479 | Data Visualization | 4 |
BSCSELE | Select 20 Credits from the list of courses shown below | 20 |
| Total Credit Hours: | 44 |
note that all courses are not offered at all campuses. Consult with your academic advisor.
Courses- Elective Choices
CS227 | Linux Programming | 4 |
CS361 | Principles of User Interface Design | 4 |
CS368 | Fundamentals of Software Requirements | 4 |
CS374 | Fundamentals of Software Design | 4 |
CS468 | Software Service Construction | 4 |
CS469 | Software Quality Assurance | 4 |
CSS200 | Principles of Network Security | 4 |
CSS250 | Security Risk Management | 4 |
CSS280 | Ethical Hacking | 4 |
CSS321 | Software Assurance | 4 |
EM200 | Introduction to Website Development | 4 |
EM218 | Web Development II | 4 |
EM228 | Scripting for the Web | 4 |
EM270 | Emerging Media and Technology | 4 |
IT304 | Computer Networks and Communications | 4 |
Total Credit Hours: 183
Area of Study
- Engineering & Computer Science