online bachelor's degree of computer science
Summer term classes start in June.
100% online learning.
Earn your degree on your schedule
$459 per credit hour.
$250 military preferred cost per credit
127 total credit hours.
learn the fundamental skills needed to solve the latest engineering, programming, and AI challenges with the online computer science degree.
Dive into the world of high tech with an online computer science program tailored to your interests, goals and past experience. With flexible online classes, you can balance your life priorities while achieving your goals.
Build broad computing expertise on top of a strong foundation.
The Bachelor of Science in Computer Science degree will help you develop a strong foundation in computing principles including algorithms, data structures, programming languages, cybersecurity, and databases. These skills can be applied to develop solutions to a wide variety of computational challenges. Courses will focus on computer theory, computing solutions, and the application of those solutions to common business and engineering problems. Each week, your instructor will help you apply what you have learned using hands-on programming assignments. Those assignments will help prepare you to code mission-critical Python programs used in enterprises around the world.
This online degree program also provides an opportunity to study computer science more broadly by choosing elective courses that will deepen your computing skills in targeted areas such as programming, data analysis and visualization, artificial intelligence, cloud computing, and DevOps — all areas of expertise that are in high demand.
Prepare for a versatile tech career.
Our online computer science degree will prepare you for a tech career in your industry. With the skills you acquire in courses such as CS 410 Algorithm Design and Analysis, you’ll learn about the code bases used in on-premise and cloud computing environments. With courses like CS 440 Artificial Intelligence, you will also learn the foundational concepts needed to program the next generation of Natural Language Processing, Machine Learning, and Deep Learning platforms using Python.
what you'll learn.
In this program, you’ll build a strong foundation in computer science—learning to design, analyze, and implement solutions to real-world computational challenges.
upon graduation, students will be able to:
- Apply knowledge of algorithms, data structures, and programming languages to solve computational challenges.
- Analyze alternative solutions to computing problems.
- Develop solutions to computational challenges that satisfy a given set of requirements.
Awards
Bellevue Stories
Computer Science degree courses
Current students please login to BRUIN and select “Academic Progress” for your curriculum requirements.
Requirements (36 credit hours)
This course provides an introduction to computer systems and provides the foundations to Computer Science. Topics include operating systems, parallel and distributed systems, communications networks, and computer architecture. Emphasis is placed on concepts and relationships between subdisciplines of computer systems.
This course provides an introduction to problem solving and computer programming using the language Python. Students will analyze problems, design and implement solutions and assess the results. Topics include fundamental programming constructs such as variables, expressions, functions, control structures and lists. Emphasis is placed on numerical and data analysis for informed decision making. Prerequisite: None
This course introduces fundamental technologies used in information systems. Students will develop a foundation in cybersecurity by learning the fundamental concepts behind cybersecurity. In addition, students will learn cybersecurity principles used in the design of systems to protect information and assets against persistent and constantly evolving threats.
This course explores the concepts underlying modern programming languages, including syntax, functions, expressions, types, polymorphism, assignment, procedures, pointers, encapsulation, classes, and inheritance. The course introduces programming paradigms, such as sequential, concurrent, object-oriented, functional, and logic programming.
The major focus of this course will be the relational, dimensional and NoSQL models. Topics include relational and dimensional modeling, business intelligence, NoSQL databases and their application, SQL, application development using databases and emerging trends. Students will prepare a small application using a commercial database management system.
This course introduces algorithms by looking at the real-world problems that motivate them. Students will use a range of design and analysis techniques for problems that arise in computing applications. The algorithm design process is emphasized as well as the role of algorithms in the broader field of computer science. The course incorporates ethics and privacy.
This course is a hands-on introduction to the design of abstract data types. Topics will include how to select and implement data structures for various problems or accomplish tasks. Fundamental data types used in computing such as lists, stacks, queues, priority queues, sets, maps, and binary trees are explored. Python language will be used for coding data structures.
This course introduces software engineering techniques that ensure development of well-designed, reliable, flexible, modular, and verified software and software systems. Development steps are examined, including software planning, specifications, coding, testing and maintenance. Additional topics include software product development, cloud-based software, microservices architecture, code management and review, agile development, and DevOps.
This course provides the theoretical basis and problem-solving experience needed to apply the techniques of descriptive and inferential statistics, to analyze quantitative data, and to improve decision making over a wide range of areas. Topics covered include descriptive statistics, linear regression, data gathering methodologies and probability, as well as confidence intervals and hypothesis testing for one and two samples. Use of technology in solving and interpreting statistical problems is emphasized. Prerequisite: MA 101 or placement via ALEKS Placement Assessment
Beyond the Core courses, choose three elective courses (9 credits). Select any three from the following courses beyond the Core requirements. Other electives may be available with academic approval.
This course explores the fundamental methods, techniques, and software used to design and develop artificial intelligence (AI) systems. Students gain experience with the practical application of AI and its enabling technologies. Included are such topics as the ethics of artificial intelligence, machine learning, language processing, expert systems, and automated planning.
This course provides students the opportunity to work on a realistic computer science project that involves coordinating with the course professor and a project advisor. The application of classroom knowledge and skills in computer science to solve real-world problems is a signature feature of this course.
This course introduces problem solving and computer programming using the C++ language. Students will analyze problems, design and implement solutions, debug their code, and assess the results. Topics include fundamental programming constructs such as variables, expressions, functions, pointers, and control structures. Emphasis is placed on low-level manipulation of data and the memory management features of the language.
This course provides an introduction to the fundamental components of encryption. Topics include the history of cryptography, public key and private key systems, hashing, and digital signatures. Topics also include the development of the Advanced Encryption Standard, the use and functionality of Pretty Good Privacy, and the Secure Socket Layer. Pre-requisite: CYBR 250 recommended
This course provides the student with the basic topics associated with controlling how resources are accessed in an information system. Topics include organizational access control models, security models, and hardware and software controls that can be used to support those models. Additionally, students will learn about access models, securing systems access with passwords, smart cards, and biometric devices to ensure data confidentiality, integrity and availability. This course also explores technologies like remote authentication and Public Key Infrastructure (PKI). Pre-requisite: CYBR 250 recommended
In order to fully analyze data, mathematical concepts need to be applied to data. This course focuses on the common statistics, algorithms, and models required for data mining and predictive analytics. Some of these concepts will include: Bayesian statistics, Bayesian models, calculus concepts to understand probability distributions, and basic linear algebra. Students will learn how to problem solve and identify the right methods to apply during their analyses. Prerequisite: MA 215 Applied Statistics
This course prepares students for the methodologies and processes required to execute a data science project. Students will learn about the critical skills required for initiating and delivering a data science project with business value: research, project management, problem solving, decision making, requirements gathering, and data analysis. This course also prepares students for making a project operational and focuses on tasks required to deploy and automate projects.
In this course, students will use various techniques and tools to explore, visualize, and present data. Students will be exposed to R, Tableau, and PowerBI to perform initial analysis and view data. Students will use statistics and programming to ask and answer insightful questions regarding data, while also learning basic storytelling and presentation concepts. Students will learn innovative ways to communicate with different levels of leadership and stakeholders.
It is estimated that data scientists spend about 80% of their time finding and cleaning data. The data currently being produced is infinitely variable in its structure, presentation, and scale. This course prepares students for dealing with this infinite variety of data and how to interact with disparate sources of data. Students will be exposed to data structures and data management via Python, SQL, and other tools teaching them how to acquire, prepare, clean, and automate dataset creation. Prerequisite: CIS 245 Intro to Programming.
Kirkpatrick Signature Series Requirements (9 credit hours)
In addition to the Major Requirements, all Bellevue University students must complete the Kirkpatrick Signature Series.
This course focuses on the political and philosophical traditions of the American republic, especially as embedded in the ideals, values, traditions, founding documents, and institutions of the United States , and considers how these traditions relate to individual citizenship and global society. Prerequisite: 60 Credit Hours
This course focuses on the creative tensions that exist between the forces of tradition and change as the country undergoes social, cultural, and political change. It considers the manner in which change can renew the vitality of a republic. Prerequisite: 60 Credit Hours
This course examines civic engagement in relation to individual freedoms and responsibilities. It fosters engaged citizens, empowered to effect positive change. Prerequisite: 60 Credit Hours
Integrative General Education Credits
Major Requirements Credits
Elective Credits
= 127 total credits*
General Education Courses
Take general education courses that do more than fill a requirement. At Bellevue University, these courses build foundational skills that apply to any career—critical thinking, qualitative reasoning, and ethical leadership. And, you can take courses individually or in course clusters, which connect three courses around one theme, building skills as you go.
About general education requirements >Elective Courses
Our broad selection of electives allows you to select courses related to your major or expand your perspective in other areas of interest.
University Accreditation
Bellevue University is accredited by the Higher Learning Commission ( hlcommission.org ), a regional accreditation agency recognized by the U.S. Department of Education.
Whether a college, university, or program is accredited is important to students receiving financial aid, employers who provide tuition assistance, donors, and the federal government.
This program is considered a non-licensure degree/certificate program and is not intended for those seeking licensure or the practice of licensed profession. This program may be relevant to multiple occupations that do not require licensure and was not designed to meet educational requirements for any specific professional license or certification.
*Consult with an admissions counselor to determine your eligible credits, as well as to verify minimum graduation requirements for this degree. Transfer credits must be from a regionally accredited college or university. Bellevue University makes no promises to prospective students regarding the acceptance of credit awarded by examination, credit for prior learning, or credit for transfer until an evaluation has been conducted.
learn on your own time, from anywhere.
Flexible schedule.
Study on your own time with courses designed to fit your busy life—whether you're working, raising a family, or serving in the military.
Reliable technical support.
Access 24/7 tech support to keep you connected and focused on learning, no matter where you are.
Dedicated online student support.
From coursework access and connectivity issues to tutoring and resume assistance, we've got you covered.
Engaging online learning.
Enjoy interactive courses designed for real-world application, with multimedia content, discussions, and hands-on projects.
grow with faculty who’ve been where you are.