M.S. Computer Science

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Upgrade your organizational impact with a master's in computer science

No ifs, ands or buts -- business depends on technology. Perhaps that explains the high demand for computer science leaders. With an 18% projected job growth rate, many organizations (from Fortune 500 companies to startups) need qualified computer science professionals to help them meet their software needs. These powerhouse organizations rely on prepared practitioners to deliver robust software solutions to help them increase efficiency, reduce turnaround time, and maximize investment.

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20-Month Completion

Finish your master's in computer science faster.

Leading Architectural Tools

Get hands-on experience with industry-standard technologies.

Customizable Program

Tailor your master's degree program to your interests.

Real-World Practitioners

Learn from experienced technology leaders.

100% Online Classes

Earn your degree around your schedule.

Game-Changing Skills

Play an important role in communicating emerging technologies to stakeholders.

Program Overview

Architect the software futures of Fortune 500 companies

If there’s one certainty in business, it’s this: business depends on technology. Which explains why the demand for computer science jobs is at an all-time high. In fact, job growth in the field is projected to increase by an astounding 18% through 2025.*

Fortune 500 companies, in particular, need computer science graduates to help them meet their large-scale software needs. That’s because getting their systems solutions right is often the difference between success and failure. These powerhouse organizations rely on qualified practitioners to deliver robust software design, architecture and implementation that increases efficiency and reduces turnaround time, all while maximizing reuse and minimizing rework.

Deepen your skills in software design and development with hands-on coursework

Franklin University's transfer-friendly online M.S. in Computer Science (MSCS) program will teach you to interface with organizational stakeholders and translate an evolving set of needs into high-level systems requirements. You'll learn how to integrate new systems within the broader hardware and software environment, too, as well as implement the solution with the agile software engineering process.

Through our practical, hands-on coursework you'll gain experience with leading implementation tools and cutting edge software analysis. And you'll be introduced to other critically needed skills, such as algorithm analysis, distributed systems, verification and testing, and database design.

Tailor your master's program around your areas of interest

Franklin lets you further increase the relevance to your job or career path with program electives in your area of interest. Choose from pathways in data analytics, cybersecurity or software systems. Other elective options include internship and independent study opportunities.

Our Computer Science master's degree program curriculum is regularly reviewed by an advisory board strongly represented by leading companies in industry, including Herb Berger, Director, Enterprise Architecture for Cardinal Health. That means what you learn at Franklin is relevant to the needs of the industry now and stays relevant over time.

Complete our career-enhancing program in as few as 20 months

With Franklin's M.S. in Computer Science program, you'll get the expertise you need to take on the technology challenges facing business. Whether you're looking to advance your career to a senior level or work with a larger organization with more sophisticated needs, Franklin's reputation will prepare you for your next move.

With no GRE requirement if you meet certain requirements, you may qualify to start immediately. Finish faster, too, by taking just two classes over five, 12-week terms. Most students are able to complete Franklin's M.S. in Computer Science program in as few as 20 months.

Earn your degree from a university built for busy adults

Earn your degree on your terms by taking classes 100% online or pursue available coursework at our main campus. Regionally accredited and nonprofit, Franklin was built from the ground-up to satisfy the needs of adult learners. Our seamless transfer process and team of academic advisors will help ease your transition to becoming a student, while our flexible course schedules help to balance your education with work, family, and life. Get started on your future today.

*Source information provided by Economic Modeling Specialists International (EMSI)

Curriculum & Course Descriptions

36 Semester Hours

Core Courses (24 hours)

COMP 620 - Analysis of Algorithms (4)

This course covers various algorithm design paradigms, mathematical analysis of algorithms, empirical analysis of algorithms and NP-completeness.

COMP 630 - Issues in Database Management (4)

This course focuses on the fundamental design considerations in designing a database. Specific topics include performance analysis of design alternatives, system configuration and the administration of a popular database system. The course also offers an in-depth analysis of the algorithms and machine organizations of database systems.

COMP 645 - Object-Oriented Design & Practice (4)

This course surveys current practices in software development and software design, especially in the area of object-oriented design. The course will examine and contrast current and leading edge methodologies and practices, including agile, extreme programming, test-driven design, patterns, aspect-oriented programming, model-driven architecture, Unified Modeling Language, and integrated development environments.

COMP 655 - Distributed Systems (4)

This course introduces the design of distributed computing systems and distributed application programming. Major concepts of distributed systems covered include: transparency, heterogeneity, process communication, consistency, fault tolerance, and security. Students will also learn to develop a real-world distributed application as a RESTful Web-service on an application server.

COMP 671 - Verification and Testing (4)

This course focuses on the issues of delivering high quality software, especially in large complex systems. Topics covered include testing strategies (black box, white box, regression, etc.), unit testing, system integration, system verification and support tools. It also will reinforce the need for requirements that are testable and traceable from the early design stages.

COMP 691 - Capstone (4)

This course, the final one in the Master of Science - Computer Science program, challenges students to research a current topic of interest in Computer Science and produce an original paper and presentation on the topic. In addition to the research paper, students are introduced to the economics of software development and the tools needed to estimate the cost of a software development project for management in a corporate environment. The last topic in the course is a discussion of ethics as it relates to Information Technology. Current topics in ethics will be discussed through the use of relevant case studies.

Electives (12 hours)

These pathways are designed to provide students with concentrated knowledge in specific areas, however, students may choose any three (12 hours) of the courses listed below to align with their personal and career goals.

Data Analytics

MATH 601 - Introduction to Analytics (4)

This course provides an introductory overview of methods, concepts and current practices in the growing field of Data Analytics. Topics to be covered include data collection, analysis and visualization as well as statistical inference methods for informed decision-making. Students will explore these topics with current statistical software. Some emphasis will also be given to ethical principles of data analytics.

DATA 605 - Data Visualization & Reporting (4)

This course focuses on collecting, preparing, and analyzing data to create visualizations, dashboards, and stories that can be used to communicate critical business insights. Students will learn how to structure and streamline data analysis projects and highlight their implications efficiently using the most popular visualization tools used by businesses today.

DATA 611 - Applied Machine Learning (4)

This course explores two main areas of machine learning: supervised and unsupervised. Topics include linear and logistic regression, probabilistic inference, Support Vector Machines, Artificial Neural Networks, clustering, and dimensionality reduction, and programming.

Cybersecurity

ISEC 610 - Information Assurance (4)

This course covers the fundamentals of security in the enterprise environment. Included are coverage of risks and vulnerabilities, threat modeling, policy formation, controls and protection methods, encryption and authentication technologies, network security, cryptography, personnel and physical security issues, as well as ethical and legal issues. This foundational course serves as an introduction to many of the subsequent topics discussed in depth in later security courses.

ISEC 620 - Software and App Security (4)

Today, software is at the heart of nearly every business from finance to manufacturing. Software pervades everyday life in expected places like phones and computers but also in places that you may not consider such as toasters, thermostats, automobiles, and even light bulbs. Security flaws in software can have impacts ranging from inconvenient to damaging and even catastrophic when it involves life-critical systems. How can software be designed and built to minimize the presence of flaws or mitigate their impacts' This course focuses on software development processes that identify, model, and mitigate threats to all kinds of software. Topics include threat modeling frameworks, attack trees, attack libraries, defensive tactics, secure software development lifecycle, web, cloud, and human factors.

ISEC 640 - Cryptography (4)

The cryptographic primitives of enciphering/deciphering and hashing are the two main methods of preserving confidentiality and integrity of data at rest and in transit. As such, the study of cryptographic techniques is of primary interest to security practitioners. This course will cover the important principles in historical and modern cryptography including the underlying information theory, mathematics, and randomness. Important technologies such as stream and block ciphers, symmetric and asymmetric cryptography, public key infrastructure, and key exchange will be explored. Finally, hashing and message authentication codes will examined as a way of preserving data integrity.

Software Systems

COMP 650 - System Architecture & Engineering (4)

This course covers topics in software systems engineering. Its scope is the design of the overall architecture for software systems with emphasis on distributed architectures. The issues in an architecture centered software development cycle and project management are addressed.

ITEC 640 - Project Management (4)

This course examines various issues related to the management of information systems. Topics include: strategic planning, organizing the technology resources, means of prioritizing and selecting information technology, staffing, personnel management, and assessment.

COMP 670 - Application of Artificial Intelligence (4)

This course focuses on the use of artificial intelligence tools and techniques in industry. Topics include cognitive psychology topics, foundation material (e.g., search algorithms, knowledge representation and AI languages) and tools (e.g., expert systems, natural language interfaces and neural networks).

COMP 610 - Internship in Computer Science (1-4)

This course provides MSCS students the opportunity to further their education with relevant work experience in the field of Computer Science. This internship is an ongoing seminar between the student, faculty and the employment supervisor. It involves a Learning Contract (Curricular Practical Training [CPT] Information, or other), periodic meetings with the faculty representative, and professional experience at a level equivalent to other electives of the MSCS program. Specification of the materials to be submitted is established in the learning contract. Participation cannot be guaranteed for all applicants.

COMP 699 - Independent Studies in Graduate Computer Science (1-4)

Independent studies courses allow students in good academic standing to pursue learning in areas not covered by the regular curriculum or to extend study in areas presently taught. Study is under faculty supervision and graded on Pass/No Credit basis. For international students, curricular practiced training may be used as an independent study with approval of program chair. (See the "Independent Studies" section of the Academic Bulletin for more details.)

Program Co-Requisites

Upon review of your completed undergraduate courses, work experience, or demonstrated competency in computer science, you may be required to complete co-requisite courses alongside your master’s degree courses.
The program chair will determine which, if any, co-requisite courses are required. The need for co-requisite courses will not delay your acceptance to the program or your ability to begin taking master’s-level courses. Your academic advisor will assist you with scheduling co-requisites to ensure smooth and steady progress toward your degree.
Graduate co-requisite courses must be completed with a grade of "B-" or better.

The Master of Science Computer Science program requires the following courses (or the equivalent from an accredited school):

COMP 111 - Introduction to Computer Science & Object-Oriented Programming (4)

This course provides an introduction to software construction using an object-oriented approach. The student learns and reflects on problem analysis, object-oriented design, implementation, and testing. To support the concepts and principles of software construction, the student will design, code, test, debug, and document programs using the Java programming language. Basic data types, control structures, methods, and classes are used as the building blocks for reusable software components. Automated unit testing, programming style, and industrial practice are emphasized in addition to the object-oriented techniques of abstraction, encapsulation, and composition.

OR COMP 501 - Foundations of Programming (4)

This course covers fundamental programming principles. Students will learn about the basic elements of a computer program such as data types, assignments, conditional branching, loops, functions, recursion, basic data structures, program debugging, and testing.

OR ITEC 136 - Principles of Programming (4)

This course covers fundamental programming principles for individuals with at least some programming background. Major themes are structured programming, problem solving, algorithm design, top-down stepwise refinement, and software lifecycle. Topics will include testing, data types, operators, repetition and selection control structures, functions, arrays, and objects. Students will design, code, test, debug, and document programs in a relevant programming language.

COMP 311 - Object-Oriented Data Structures & Algorithms II (4)

This course is the third of four courses using the object-oriented approach to software construction. The student learns and reflects on non-linear data structures, recursive algorithms, algorithm efficiency, and design patterns. To support the concepts and principles of software construction, the student will design, code, test, debug, and document programs using the Java programming language. Implementation and analysis of sets, maps, balanced binary search trees, heaps, hashing and hash tables, graphs and graph algorithms, and efficient sorting algorithms are addressed.

OR COMP 502 - Foundations of Data Structures & Algorithms (4)

This course continues the objected-oriented approach to software construction and focuses on non-linear data structures and algorithms in Computer Science. The student learns and reflects on advanced object-oriented techniques, algorithm efficiency, and data structures. To support the concepts and principles of software construction, the student will design, code, test, debug, and document programs using the Java programming language. Topics include: I/O, exception handling, non-linear data structures (sets, maps, balanced binary search trees, heaps, hashing and hash tables, and graphs) and efficient sorting algorithms.

MATH 320 - Discrete Mathematics (4)

This course introduces students to fundamental algebraic, logical and combinational concepts in mathematics that are needed in upper division computer science courses. Topics include logic; sets, mappings, and relations; elementary counting principles; proof techniques with emphasis on mathematical induction; graphs and directed graphs; Boolean algebras; recursion; and applications to computer science. Please note: A book fee will be included in your tuition charges for required course materials.

OR MATH 503 - Foundations of Mathematics for Computing (4)

This course introduces students to fundamental algebraic, logical, and combinational concepts in mathematics that are needed in upper division computer science courses. Topics include integer representation; algorithms; modular arithmetic and exponentation; discrete logarithms; cryptography; recursion; primality testing; number theory; graphs and directed graphs; trees; and Boolean Algebra.

Program Details

Tuition Costs

2020 - 2021 Tuition	Cost Per Credit
Standard tuition per credit hour	$670
Current service members	$536
Graduate Prerequisite Courses (500 level)	$398

Program Learning Outcomes

A learning outcome map functions as a roadmap to help guide students' progress through their program of study. It shows where each outcome is Introduced (I), Reinforced (R), and Assessed (A) within the program's curriculum.
	1	2	3
COMP 620		R
COMP 630		R
COMP 645	I, R, A	I, R, A	I, R, A
COMP 655	R	R
COMP 671	R	R	R
COMP 691	R, A	R, A	R, A

Degree Requirements

To be awarded a graduate degree, students must:

Successfully complete all required curriculum courses.
Maintain a minimum cumulative grade point average (GPA) of 3.00.
Complete the residency requirement:
1. M.S. - Computer Science students must earn in residence at Franklin University at least 24 of the 36 required credits.
Complete the payment of all requisite tuition and fees;
Not to be under disciplinary dismissal due to academic dishonesty or violation of Student Code of Conduct.

Transfer credit awarded based on experiential learning shall not count toward the residence requirement at Franklin University.

Admission Requirements

The admission process reflects Franklin University’s efforts to clearly identify the performance standards that can help predict student success in graduate level study. The selection criterion for Franklin’s graduate programs, as determined by faculty, emphasizes academic ability, contributory work experience, and personal qualities and characteristics.

Requirements for admission include having earned a bachelor's degree from a regionally accredited institution. The bachelor's degree final cumulative GPA must be at least a 2.75 on a 4.0 scale, otherwise a graduate entrance exam may be required. The candidate’s work history, references, and other personal qualities and characteristics will be considered as well if the GPA requirement is not met.

English Language Testing & TOEFL IELTS

Prospective students must demonstrate English Language Proficiency. The requirement is met through any of the following:

The applicant is a citizen of a country where English is the official language.*
The applicant has received a bachelor’s degree (or higher) from an institution located in an English-speaking country in which the courses were taught in English.*
The applicant has earned appropriate scores on language proficiency exams taken within the last two years, as listed in the Academic Catalog.

*For more information about English proficiency, including a list of English-speaking nations, please visit our International Students section.

Program Advisory Board

The University employs a team approach to planning, developing and maintaining its academic curriculum. An essential element of this process – and a key to the institution’s quality assurance practices – is the Program Advisory Board (and the associated Alumni Advisory Board). A diverse array of business and industry leaders make up these discipline-specific boards that provide guidance on theory-to-practice ideas, global business perspectives, and emerging topics in the field. Each academic year, Program Advisory Boards meet with Division Chairs and faculty for lively and engaged conversations, thus bringing members’ substantial professional experience and expertise into the classroom. In addition, some Division Chairs elect to engage Program Advisory Board members in the assessment of academic program outcomes.

Computer Science Programs Advisory Board
Name	Organization	Title
Venkat Ashok	Quest Communications	Information Technology
Herbert Berger	Cardinal Health	Enterprise Architect
Sally Griffiths	Battelle Memorial Institute	Production Services Manager
Mark Juras	Great Migrations, LLC	Managing Partner
Shekhar Mahajan	Nationwide Insurance	CTO, Corporate Applications
Doyt Perry, PhD	Muskingum College	Associate Professor of Informatics
David Sayre	Sayre Systems, LLC	Consultant
Paul Varner	Nationwide Insurance	Consulting IT Architect
David Vazquez	Nationwide Insurance	Director, IT Applications
Guru Vasudeva	Nationwide Insurance	SVP & Enterprise CTO
Mary Vaughn	Columbus State Community College	Chair, Integrated Media and Technology
Raymond Waite, Jr.	IBM	Manager, Performance and Systems Engineering
Byron White	Chemical Abstracts Services	Manager, Enterprise Business Systems Development

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Employment Outlook

18%

From 2018-2029 jobs in Computer Science are expected to increase by 18%

All Occupations

2018	3,839,682 jobs
2029	4,539,861 jobs

Show Details >

Computer and Information Systems Managers

2018	408,448 jobs
2029	473,023 jobs

Software Developers, Applications

2018	945,844 jobs
2029	1,231,663 jobs

Software Developers, Systems Software

2018	424,521 jobs
2029	488,744 jobs

Computer User Support Specialists

2018	717,615 jobs
2029	829,783 jobs

Computer Occupations, All Other

2018	424,209 jobs
2029	486,714 jobs

Source information provided by Economic Modeling Specialists International (EMSI).

Knowledge & Skillsets

Gain in-demand skills sought by employers with curriculum that teaches you:

Systems Architecture

Translate business needs into high-level system requirements based on constraints, such as cost and schedule
Expand and adapt architecture in support of growing user base and increasing application functionality
Use best practice software development methodologies to ensure technical solutions development and implementation within specified timelines
Set development, interface, and coding standards
Evangelize software development methodologies through training, role modeling, and influencing product teams
Oversee design, implementation, administration, and support of systems architecture, and infrastructure products and services to ensure security, availability, reliability, and scalability
Create systems architecture design using state-of-the-art, rules-based architecture, object-oriented component analysis, and development and technologies, such as OOA, OOD, UML, and COBRA
Propose necessary hardware and operating system cost savings, platform needs, communication protocols, middleware, interfaces, and algorithms
Design software to maximize efficiency of current and planned hardware architectures
Develop, maintain, and govern enterprise architecture (EA), including defining architecture review processes and integrating processes with related business methodologies and strategies

Algorithm Analysis

Evaluate algorithm efficiency and determine the most elegant program logic for problems of varying complexity
Establish algorithm requirements in support of software development roadmaps
Assist in the development of advanced algorithms for next-generation functions
Prototype, design, develop, unit test, and release software-utilizing algorithms in support of goals, strategies, technologies, and concepts

Distributed Systems

Build and maintain high-performance distributed systems to meet organizational needs
Create efficient data structures and analyze distributed algorithms to enable scalable applications
Develop scalable, robust, distributed data architecture to support data analytics in real time
Solve technical challenges and issues around distributed systems
Process large amounts of data, and tackle challenging technical problems

Acceptance Testing

Create detailed plans, cases, and scripts to test applications
Perform functional, unit, and integration tests
Ensure software meets design specifications and performance standards
Review requirements specifications to ensure testability and compliance with quality control standards
Define and track quality assurance metrics, such as defects, defect counts, test results and test status

Database Design & Administration

Develop dynamic, data-driven applications through mastery of relational database design, complex SQL queries, and transaction processing
Write SQL database queries of medium to high complexity in support of data analysis and technical programming
Apply relational database design best practices to efficiently build data models
Implement data models, database designs, data access, and table maintenance codes
Analyze large collections of data in order to inform and apply association rules and other techniques, such as genetic encoding, classification hierarchies, and regression analysis to decision making
Apply relational algebra to the optimization of queries using heuristics
Utilize data mining techniques to discover knowledge in large data collections
Apply refactoring techniques to modify and improve database designs

Frequently Asked Questions

How long does it take to get a M.S. - Computer Science degree?

Franklin's master's degree programs are specifically designed for busy, working adults -- that means you could finish your degree in as few as 20 months.

When can I start a M.S. - Computer Science degree?

Start taking the next step in your career. Begin your Franklin online master's degree program in January, May or September.

How much will my M.S. - Computer Science degree cost?

Franklin University offers a quality education at a competitive cost so you can afford to invest in your future. Our per credit hour tuition rates (vs. per year or per term rates) enable you to get a realistic estimate of exactly how much your degree will cost. Our 2019-2020 tuition rate is $670 per credit hour. Ask our helpful staff about available financing options and financial aid programs.

What is a M.S. - Computer Science degree?

Franklin University's M.S. Computer Science (MSCS) is a master's-level degree program designed to advance your skills and career path. In this program, you'll learn both the theoretical and practical application skills needed to participate in the development of emerging technologies.

What can you do with a M.S. - Computer Science degree?

As a graduate of Franklin University's M.S. Computer Science master's degree program, you'll be ready to take the next step in your career, assuming a software project leadership role that includes planning processes and products, designing software architecture, and sharing software development progress with key stakeholders.

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Franklin University is committed to being an inclusive community free from all forms of discrimination and harassment.

Upgrade your organizational impact with a master's in computer science

Take the next step toward your degree!

20-Month Completion

Leading Architectural Tools

Customizable Program

Real-World Practitioners

100% Online Classes

Game-Changing Skills

Program Overview

Architect the software futures of Fortune 500 companies

Deepen your skills in software design and development with hands-on coursework

Tailor your master's program around your areas of interest

Complete our career-enhancing program in as few as 20 months

Earn your degree from a university built for busy adults

Curriculum & Course Descriptions

Free Report: Top 10 Master's Degrees

Program Details

Recommended Application Deadlines

Entrance Exam

English Language Testing & TOEFL IELTS

Computer Science Programs Advisory Board

Request Free Information!

Request Information

Employment Outlook

From 2018-2029 jobs in Computer Science are expected to increase by 18%

Source information provided by Economic Modeling Specialists International (EMSI).

Knowledge & Skillsets

Frequently Asked Questions

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Upgrade your organizational impact with a master's in computer science

Take the next step toward your degree!

20-Month Completion

Leading Architectural Tools

Customizable Program

Real-World Practitioners

100% Online Classes

Game-Changing Skills

Architect the software futures of Fortune 500 companies

Deepen your skills in software design and development with hands-on coursework

Tailor your master's program around your areas of interest

Complete our career-enhancing program in as few as 20 months

Earn your degree from a university built for busy adults

Free Report: Top 10 Master's Degrees

Recommended Application Deadlines

Entrance Exam

English Language Testing & TOEFL IELTS

Computer Science Programs Advisory Board

Request Free Information!

Request Information

We're Sorry

From 2018-2029 jobs in Computer Science are expected to increase by 18%

Source information provided by Economic Modeling Specialists International (EMSI).

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SHORTCUTS:

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