BS in Computer Science
Fairfax University of America
Key Information
Campus location
Fairfax, USA
Languages
English
Study format
On-Campus
Duration
4 years
Pace
Full time, Part time
Tuition fees
USD 6,330 / per semester *
Application deadline
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Earliest start date
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* up to 21 credit hours per semester tuition fee. Additional fees apply
Scholarships
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Introduction
The Bachelor of Science in Computer Science (BSCS) program educates and trains students to create and implement solutions for information systems-based needs and problems in research, commercial, financial, governmental, or other types of organizations. The approach of this degree program is to integrate theoretical and practical aspects of computer science and technology. The program provides a blend of theory and applications, preparing students for a variety of Computer Science careers in industry, government, and academia; and developing the foundation for continuing education and growth in the field of Computer Science.
The future of Computer Science
The core of this program focuses on the development of the skills required of competent and capable individuals in the workforce. The goal is to help students to develop the leadership skills and knowledge of organizations in order to make a positive social impact. In the Leadership Core, students develop an understanding of how organizations function and how change occurs within these organizations. Students take courses from three domain areas including Leadership Development (LD), Organizations and Contexts (OC), and Organizational Psychology (OP).
Areas of Focus
Artificial Intelligence (AI) and Machine Learning (ML)
Develops and demonstrates an understanding of artificial intelligence techniques, algorithms, knowledge base building, and heuristic search.
Networking and Cybersecurity
Develops an understanding of cybersecurity protocols and techniques to secure and protect sensitive information and financial assets following the NIST Standards as well as implements and maintains robust information security systems and networks that protect organizations from cyberattacks.
Data Science (DS)
Focuses on the application of data science principles and methods to solve real-world problems as well as demonstrates and executes statistical analysis of complex data.
Career Opportunities
- Digital Forensics Analyst
- Cybersecurity Analyst
- Cybersecurity Engineer
- Network System Administrator
- AI Engineer
- Machine Learning Engineer
- Machine Learning Data Developer
- AI Interaction Designer
- Computer Systems Analyst
- Software Developer
- Database Developer
- Database Administrator
- QA Tester
Curriculum
Computer Science Micro-Credentials
What are micro-credentials?
They are mini-qualifications that demonstrate skills, knowledge, and/or experience in a given subject area or capability.
- Advanced Artificial Intelligence and Machine Learning (AAI)
- Advanced Computer Networks (ACN)
- Advanced Cybersecurity (ACS)
- Advanced Data Science (ADS)
- Advanced Programming (AP)
- Advanced Software Application Development (ASDE)
- Advanced System Design (ASD)
- Essentials of Artificial Intelligence and Machine Learning (EAI)
- Essentials of Computer Ethics (ECE)
- Essentials of Computer Networks (ECN)
- Essentials of Cybersecurity (ECS)
- Essentials of Data Science (EDS)
- Essentials of Programming (EoP)
- Essentials of Software Application Development (ESAD)
- Essentials of System Design (ESD)
Curriculum
General Education Department Courses
Arts and Humanities Division (3 Courses -9 Credit Hours)
- HUMN 101 Introduction to the Arts and Humanities
- HUMN 105* Foundations of Learning and Being
- HUMN 125* Worldviews and Models of Action
- PHIL 101 Philosophy
- RLGN 110 Comparative Religion
Communications Division (2 Courses – 6 Credit Hours)
- COMM 110 Oral Communication Skills
- ENGL 120 Academic Writing and Research
Mathematical Sciences Division (1 Course – 3 Credit Hours)
- MATH 160 Pre-Calculus
- MATH 165 Calculus I
Natural Sciences Division (2 Courses – 6 Credit Hours)
- BIOL 101 General Biology
- CHEM 101 General Chemistry
- GEOL 101Introduction to Geology
- PHYS 101 College Physics
Social Sciences and Cross-Cultural Studies Division (3 Courses – 9 Credit Hours)
- GOVT 120 Comparative Government
- GOVT 130 American Society and Politics
- GEOG 101 World Geography
- HIST 101 World History
- INCS 300* The Context of Global Citizenship
- INCS 325* Being a Global Citizen
- SOCI 101 Sociology
- PSYC 101 Psychology
Transformative Learning and Leadership in Practice Division (3 Courses – 9 Credits)
- TLLP 150 Practices of Learning and Being
- TLLP 200 Designing a Life of Self-Fulfillment
- TLLP 400 Designing a Life of Possibilities – Concepts, Tools, and Processes of Thinking
*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
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Specialization
AI and ML Specialization: (6 Courses – 18 Credit Hours)
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Networking and Cybersecurity Specialization: (6 Courses – 18 Credit Hours)
- COMP 360 Switching and Routing Protocols
- COMP 365* Cybersecurity and Information Assurance
- COMP 370* Essentials Digital Forensics
- COMP 391 Internship in Networking
- COMP 392 Internship in Cybersecurity
- COMP 410/510^ Intrusion Detection and Prevention Systems
- COMP 411/511^ Cloud Security
- COMP 412/512^ Special Topics in Networking
- COMP 419/519^ Special Topics in Cybersecurity
- COMP 430 Ethical Hacking
- COMP 431 Cryptography and Ciphering
- COMP 429 Operating Systems Security
- COMP 433/533^ IoT and Smart Cities Security
- COMP 434/534^ Information Risk Management
- COMP 436 Cybersecurity Governance and Compliance
- COMP 486 Comp TIA Network+ and Test Preparation
- COMP 487 Comp TIA Security+ and Test Preparation
Data Science Specialization: (6 Courses – 18 Credit Hours)
- COMP 362 Data Science Mathematical Foundations
- COMP 363* Data Science Algorithmic Foundations
- COMP 364 Statistics Essential for Data Science
- COMP 396 Internship in Data Science
- COMP 440* R Programming for Data Science
- COMP 441 Statistical and Computational Foundations of Machine Learning
- COMP 442/542^ Numerical Analysis
- COMP 443/543^ Data-Intensive Distributed Computing
- COMP 444/544^ Special Topics in Data Science
- COMP 484 Microsoft Certified Azure Data Scientist Associate
- COMP 485 SAS Certified Data Scientist
*Indicates required course.
^Can be taken for graduate course credit.
Note: Students who wish to take a course that is offered by 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.