Bachelor of Science in Computer Science (BSCS)
Degree Program Overview
Computer science is concerned with the systematic study of algorithms for describing and transforming information and designing solutions to produce outcomes. Innovative computing solutions have provided the basis for advances in other fields. Computer science offers practitioners the chance to make real contributions that benefit society at large and are vital for virtually every organization, including commercial businesses, financial firms, government agencies, and research institutions. At Fairfax University of America, our Bachelor of Science in Computer Science (BSCS) program teaches students to design and implement solutions for challenges within information systems at various organizations.
Computer Science Degree Program Objectives
As with all our undergraduate programs, the overarching goal of the computer science degree program is to provide students with the organizational knowledge and leadership skills necessary to be competent workers making constructive impacts in their chosen industries. The Leadership Core of this program sheds light on how organizations operate and the many changes that occur within them. This core consists of the three following domain areas:
Leadership Development (LD): Students learn to be effective leaders of companies. The program helps them strengthen skills in multiple fields, including project supervision, decision making, and networking.
Organizations and Contexts (OC): Students learn to look at an organization’s structure, performance goals, strengths, challenges, and parties of interest. They also learn to consider how external and internal factors affect an organization.
Organizational Psychology (OP): Industrial-organizational psychology looks at how people behave in occupational environments.
BSCS Degree Program Course Work
The BSCS program features a mix of theoretical and practical training in computer science and technology. This instruction enables students to seek multiple careers in academic, governmental, and industrial settings and creates a foundation for continuing education in computer science. Along with core computer science courses, students also take classes in specialty areas and complete general studies in the following subjects:
· Arts and humanities
· Communications
· Mathematical sciences
· Natural sciences
· Social sciences and cross-cultural studies
· Transformative learning and leadership in practice
Students enrolled in the BSCS degree program will complete 41 courses and attain 120 credits. To find further information about specific computer science classes, we provide detailed course descriptions. This list outlines the learning objectives and prerequisites for each course.
BSCS Degree Program Areas of Focus
The BSCS program also offers specialization courses in some of the most relevant topics in computer science. The three areas of focus for this degree program are:
Artificial Intelligence (AI) and Machine Learning (ML)
These courses give students an understanding of the algorithms and methods used with AI. Students also learn strategies for heuristic search and building their knowledge base.
Networking and Cybersecurity
This focus area discusses cybersecurity practices and tactics students can implement to protect sensitive data and financial assets according to National Institute of Standards and Technology (NIST) standards. Additionally, students will learn how to employ and manage robust information security systems and networks to defend organizations against cyber attacks.
Data Science (DS)
After studying this specialization, students can apply data science principles and techniques to solve real-world issues they may experience in their careers. They also will know how to perform statistical analyses of complex datasets.
What are Micro-Credentials?
Students enrolled in our computer science degree program can attain further education and potentially advance their career opportunities by earning micro-credentials. These cost-effective, flexible, and brief certifications provide students with knowledge and experience in a specific capability or field of study. Our Office of Micro-Credentials offers the following mini-qualifications for computer science majors:
COMPUTER SCIENCE MICRO-CREDENTIALS
Career Outlook With A Computer Science Degree
In today’s digital world, computer science is integral to the success of many businesses. Therefore, having a bachelor’s degree in computer science allows you to fill multiple positions across numerous industries. The following list highlights some of the most rewarding careers for computer science students, as well as median salaries from the U.S. Bureau of Labor Statistics (BLS):
· Computer and information research scientist ($126,830)
· Network architect ($116,780)
· Software developer ($110,140)
· Information security analyst ($103,590)
· Database administrator ($98,860)
· Computer programmer ($89,190)
· Web developer ($77,200)
Earn Your Bachelor of Science in Computer Science Degree
Receive an affordable and student-centered computer science education by applying to the BSCS program at Fairfax University of America. The curriculum will give you the competencies required to achieve a successful career and be a transformative leader in today’s multifaceted, global society. Our non-profit academic institution is giving students access to employment opportunities at diverse organizations.
To learn more about our computer science degree program, request information online today. You also can complete an application to start your educational journey.
BSCS CURRICULUM OVERVIEW
| Area | Number of Courses | Credits |
| General Education Department Courses | 14 | 42 |
| Fundamental Courses | 21 | 60 |
| Specialization | 6 | 18 |
| Total | 41 | 120 |
General Education Courses
Arts and Humanities Division (3 Courses -9 Credit Hours)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| HUMN 101 | Introduction to the Arts and Humanities | None | 3 | |
| HUMN 105* | Foundations of Learning and Being | None | PR | 3 |
| HUMN 125* | Worldviews and Models of Action | None | PR, GC, DMPS | 3 |
| PHIL 101 | Philosophy | None | 3 | |
| RLGN 110 | Comparative Religion | None | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Communications Division (2 Courses – 6 Credit Hours)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| COMM 110 | Oral Communication Skills | None | 3 | |
| ENGL 120 | Academic Writing and Research | None | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Mathematical Sciences Division (1 Course – 3 Credit Hours)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| MATH 160 | Pre-Calculus | None | 3 | |
| MATH 165 | Calculus I | None | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Natural Sciences Division (2 Courses – 6 Credit Hours)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| BIOL 101 | General Biology | None | 3 | |
| CHEM 101 | General Chemistry | None | 3 | |
| GEOL 101 | Introduction to Geology | None | 3 | |
| PHYS 101 | College Physics | None | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Social Sciences and Cross-Cultural Studies Division (3 Courses – 9 Credit Hours)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| GOVT 120 | Comparative Government | None | 3 | |
| GOVT 130 | American Society and Politics | None | 3 | |
| GEOG 101 | World Geography | None | 3 | |
| HIST 101 | World History | None | 3 | |
| INCS 300* | The Context of Global Citizenship | None | GC | 3 |
| INCS 325* | Being a Global Citizen | None | GC, SP | 3 |
| SOCI 101 | Sociology | None | 3 | |
| PSYC 101 | Psychology | None | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Transformative Learning and Leadership in Practice Division (3 Courses – 9 Credits)
| Code | Course Title | Prerequisites | Microcredentials | Credits |
| TLLP 150 | Practices of Learning and Being | None | DMPS | 3 |
| TLLP 200 | Designing a Life of Self-Fulfillment | None | PR | 3 |
| TLLP 400 | Designing a Life of Possibilities – Concepts, Tools, and Processes of Thinking | None | DMPS | 3 |
*Indicates a required course. This course continues the “Learning to Learn, Learning to Be” approach taken in our Transformative Learning and Leadership in Practice (TLLP) curriculum.
Required Courses
| Code | Course Title | Prerequisite | Microcredentials | Credits | |
| MC | Certification | ||||
| COMP 109 | Computer Algorithm and Programming Logic Using Python | None | EoP | 3 | |
| COMP 121 | Object Oriented Programming | COMP 109 | EoP | Certified Associate in Python Programming | 3 |
| COMP 130 | Ethical, Social, and Legal Aspects of Computing | None | ECE | 3 | |
| COMP 157 | Seminar I | None | 1 | ||
| COMP 231 | Discrete Mathematical Methods for Computing | None | 3 | ||
| COMP 250 | Computer Architecture | COMP 109 | ESD | 3 | |
| COMP 260 | Introduction to Operating Systems | COMP 109 | ESD | 3 | |
| COMP 270 | Essentials of Networking | COMP 109 | ECN | 3 | |
| COMP 280 | Comp TIA A+ and Test Preparation | None | ESD | A+ | 3 |
| COMP 329 | Data Structures and Algorithm Analysis | None | EoP | 3 | |
| COMP 345 | Introduction to Computer Security | None | ECS | 3 | |
| COMP 350 | Database Concepts | None | ESAD | 3 | |
| COMP 361 | Introduction to Data Science | None | EDS | 3 | |
| COMP 375 | Human Computer Interaction | COMP 250 | ESAD | 3 | |
| COMP 380 | Wireless and Mobile Security | None | ECS & ECN | 3 | |
| COMP 390 | Seminar II | COMP157 | 1 | ||
| COMP 450 | Research and Analytic Skills | None | EoP | 3 | |
| COMP 499 | Senior Project and Seminar | COMP 390 | AAI | 4 | |
| TLLP 250 | Designing Your Career to Find Purpose, Meaning, and Success | None | CAR, SP | None | 3 |
| TLLP 275 | Pursuing Social Impact Throughout Your Career | None | CAR, SP | None | 3 |
| TLLP 425 | Designing a Life of Possibilities – Career Planning and Leadership | None | CAR | None | 3 |
SPECIALIZATION COURSES
AI and ML Specialization: (6 Courses – 18 Credit Hours)
| Code | Course Title | Prerequisite | Microcredentials | Credits | |
| MC | Certification | ||||
| COMP 340 | Computer Graphics | None | ESD | 3 | |
| COMP 376 | Artificial Intelligence Principles | None | EAI | 3 | |
| COMP 377* | Machine Learning Principles | None | EAI | 3 | |
| COMP 378 | Decision-Making and Robotics Principles | None | 3 | ||
| COMP 379* | Human-AI Interaction | None | EAI | 3 | |
| COMP 393 | Internship in AI | Minimum of 90 credits | ESD | 3 | |
| COMP 394 | Internship in Machine Learning | Minimum of 90 credits | ADS | 3 | |
| COMP 413/513^ | Robotics Design and Programming | COMP 378 | ASD | 3 | |
| COMP 414 | Big Data Analytics | None | EAI & AP | 3 | |
| COMP 415 | Natural Language Processing | None | 3 | ||
| COMP 416 | Computer Vision and Image Processing | None | ADS | 3 | |
| COMP 417/517^ | Special Topics in AI | Minimum of 90 credits | ESAD | 3 | |
| COMP 418/518^ | Special Topics in ML | Minimum of 90 credits | ESAD | 3 | |
| COMP 420 | Creativity in Machine Learning | COMP 330 | AAI | 3 | |
| COMP 421/521^ | Smart Devices Design and Applications | COMP 330 | AAI | 3 | |
| COMP 422/522^ | Data Mining | COMP 330 | AAI | 3 | |
| COMP 480 | AWS Test Preparation for Cloud Practitioner Certificate | None | EAI & ESD | AWS | 3 |
| COMP 487 | IBM AI Engineering Professional Test Preparation | None | ADS | IBM AI | 3 |
*Indicates required course.
^Can be taken for graduate course credit.
NOTE: Students who wish to take a course that is offered in another specialization may petition to do so to their advisor by providing justification for the relevance of the addition as part of their professional trajectory, their intended project, and/or personal interest. A maximum of 2 courses from other areas can be applied to a specialization.
Networking and Cybersecurity Specialization: (6 Courses – 18 Credit Hours)
| Code | Course Title | Prerequisite | Microcredentials | Credits
|
|
| MC | Certification | ||||
| COMP 360 | Switching and Routing Protocols | None | ECN | 3 | |
| COMP 365* | Cybersecurity and Information Assurance | None | ECS | 3 | |
| COMP 370* | Essentials Digital Forensics | None | ECS | 3 | |
| COMP 391 | Internship in Networking | Minimum of 90 credits | ECN | 3 | |
| COMP 392 | Internship in Cybersecurity | Minimum of 90 credits | ECS | 3 | |
| COMP 410/510^ | Intrusion Detection and Prevention Systems | None | ACN &ACS | 3 | |
| COMP 411/511^ | Cloud Security | None | ACS | 3 | |
| COMP 412/512^ | Special Topics in Networking | None | ACN | 3 | |
| COMP 419/519^ | Special Topics in Cybersecurity | None | ACS | 3 | |
| COMP 430 | Ethical Hacking | None | ECS & ECE | CEH | 3 |
| COMP 431 | Cryptography and Ciphering | None | ACS | 3 | |
| COMP 429 | Operating Systems Security | COMP 260 | ESD & ACS | 3 | |
| COMP 433/533^ | IoT and Smart Cities Security | None | ACS | 3 | |
| COMP 434/534^ | Information Risk Management | None | ACS | 3 | |
| COMP 436 | Cybersecurity Governance and Compliance | None | 3 | ||
| COMP 486 | Comp TIA Network+ and Test Preparation | COMP 270 | ACN | Network+ | 3 |
| COMP 487 | Comp TIA Security+ and Test Preparation | COMP 345 | ACS | Security+ | 3 |
*Indicates required course.
^Can be taken for graduate course credit.
NOTE: Students who wish to take a course that is offered by in another specialization may petition to do so to their advisor by providing justification for the relevance of the addition as part of their professional trajectory, their intended project, and/or personal interest. A maximum of 2 courses from other areas can be applied to a specialization.
Data Science Specialization: (6 Courses – 18 Credit Hours)
| Code | Course Title | Prerequisite | Microcredentials | Credits | |
| MC | Certification | ||||
| COMP 362 | Data Science Mathematical Foundations | Non | ESD | 3 | |
| COMP 363* | Data Science Algorithmic Foundations | None | ESD | 3 | |
| COMP 364 | Statistics Essential for Data Science | STAT 200 | ESD | 3 | |
| COMP 396 | Internship in Data Science | Minimum of 90 credits | ADS | 3 | |
| COMP 440* | R Programming for Data Science | COMP 120 | AP | 3 | |
| COMP 441 | Statistical and Computational Foundations of Machine Learning | STAT 20 | 3 | ||
| COMP 442/542^ | Numerical Analysis | COMP 23 | 3 | ||
| COMP 443/543^ | Data-Intensive Distributed Computing | COMP 250 | ADS | 3 | |
| COMP 444/544^ | Special Topics in Data Science | Minimum of 90 credits | ADS | 3 | |
| COMP 484 | Microsoft Certified Azure Data Scientist Associate | None | EDS | Microsoft Azure | 3 |
| COMP 485 | SAS Certified Data Scientist | None | ADS | SAS | 3 |
*Indicates required course.
^Can be taken for graduate course credit.
NOTE: Students who wish to take a course that is offered by in another specialization may petition to do so to their advisor by providing justification for the relevance of the addition as part of their professional trajectory, their intended project, and/or personal interest. A maximum of 2 courses from other areas can be applied to a specialization.