Computer Science Bachelor's Degree Program

This course introduces students to the Franklin University community and provides strategies for successful transition to and participation in that community. Topics include University resources and procedures, strategies for advancing communication skills, the use of electronic tools to participate in virtual environments, and the development of an academic and career plan.

This course prepares students to be successful lifelong learners both academically and in their chosen careers. Franklin courses require a high level of self-directed learning and focus on skills required in the workplace and the classroom that are easily transferable between the two environments. The course includes strategies for advancing communication skills, including the use of electronic tools to participate in virtual environments. The assignments and activities in the course are created to closely simulate teamwork found in the workplace.

This public-speaking course emphasizes the fundamentals of extemporaneous speaking. Skill-building activities and assignments focus on research, organization, reasoning, style and delivery of presentations as well as listening and audience engagement.

By using applied critical and creative thinking, students in this course will develop a set of communication skills that will enhance their personal and professional relationships and endeavors. This course will focus on skill development in key areas such as self, perception, listening, verbal messages, conversations, relationships, conflict management, persuasion, and public speaking.

This is an intermediate course focusing on the composition of research papers. Students in this course prepare to be active participants in professional discourse communities by examining and practicing the writing conventions associated with their own fields of study and work. By calling attention to the conventions of disciplinary writing, the course also prepares students for upper-division college writing and the special conventions of advanced academic discourse. Course activities include three extended research papers, semi-formal writing addressing interdisciplinary communication, and readings fostering critical engagement with disciplinary conversations.

This course introduces the student to statistics with business applications. The course covers both descriptive and inferential statistics. Topics included are: measures of central tendency; measures of dispersion; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing. These topics will be covered using a basic knowledge of algebra and Microsoft Excel. Note, this course has proctored exam(s).

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. Note, this course has proctored exam(s).

This course is one of four courses that holistically explore the structure of computational systems. This course deals with the nature of computer hardware. The course will cover the structure of current computer systems at the level of functional organization, representation of data and programs, the design of the memory hierarchy, and the design of the I/O system. The course will introduce basic assembly language. Note, this course has proctored exam(s).

This course serves as an introduction to the function, design, administration, and implementation of computer networks. Topics include network infrastructure, architecture, protocols, applications, and the OSI networking model. Note, this course has proctored exam(s).

This course covers fundamental concepts necessary for the design, use, implementation and administration of database systems. The course will stress the fundamentals of database modeling and design, the languages and facilities provided by database management systems, and some techniques for implementing and administering database systems. Note, this course has proctored exam(s).

This is the first practicum course in the Computer Science program. It provides experience in an on-going software development project. A student at this level will be given an assignment in a team similar to that of a new hire in industry. The software development project will require the student to apply industry best practices in completing an assignment for the project.

The Internet has changed dramatically; so have the activities that are dependent on it in some shape or form. Understanding the need for security, it's influence on people, businesses and society, as well as business drivers is critical. The course also covers malicious attacks, threats and vulnerabilities common to the world of security, as well as access controls, and methods to assess and respond to risks. Hands-on labs accompany the various concepts that are taught.

Many organizations today utilize computers and information systems to store, organize, analyze, and summarize data to solve problems. As a result, computing is a tool that can benefit students in many different fields. At the heart of solving problems with computers is the study of structured thinking using algorithms. This course is designed for students with no prior programming experience and teaches the building blocks of algorithms, including variables, expressions, selection and repetition structures, functions and parameters, and array processing. Note, this course has proctored exam(s).

This course explores the concepts of cloud computing, including financial impacts and business value, financial requirements, deployment, risks, and security. Hands-on exercises help students to gain experience with cloud computing environments, identifying technical and security requirements for given deployment scenarios, implementing the proposed cloud deployment scenario, and troubleshooting technical issues of existing cloud computing scenarios.

This course continues the object-oriented approach to software construction. The student learns and reflects on advanced object-oriented techniques, algorithm efficiency, class hierarchies, 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. Design principles, I/O, exception handling, linear data structures (lists, stacks, and queues), and design patterns are emphasized in addition to the object-oriented techniques of inheritance and polymorphism. Note, this course has proctored exam(s).

This course continues the object-oriented approach to intermediate-level software development. The student will learn and reflect on fundamental object-oriented analysis techniques, basic design patterns, and linear data structures such as lists and queues. To support the concepts and principles of software development, the student will design, code, test, debug, and document programs using the Java programming language. Note, this course has proctored exam(s). This exams requires additional technology, if student uses online proctoring.

This course provides an introduction to server-based programming using an object-oriented approach. The student learns and reflects on two- and three-tier software architectures, separation of responsibility, design patterns, and web frameworks. To support the concepts and principles of server-based software construction, the student will design, code, test, debug, and document programs using the Java programming language. Swing-based GUI clients, XHTML clients, XML, JDBC, Java Server Pages and Java Servlets, are used as the implementation mechanisms for Model 1 and Model 2 Web architectures. Note, this course has proctored exam(s).

This course introduces the major topics of operating systems such as file systems, IO, virtual memory, and scheduling. The application of operating systems is shown in mobile and personal devices as well as in servers and large scale processing systems. In addition, the student is given an introduction to multi-process and threaded applications and the resultant need to apply synchronization to avoid deadlock. Note, this course has proctored exam(s).

This is the second practicum course in the Computer Science program. It provides experience in an on-going software development project. A student at this level will be given an assignment in a team similar to that of an experienced team member or as a team leader in industry. The software development project will require the student to apply industry best practices in completing an assignment for the project.

This is the third practicum course in the Computer Science program. It, like the first two practicum experiences, is an on-going software development project. A student at this level will be given an assignment at the most senior level, requiring planning and overall coordination tasks. Design tasks of extreme complication are also candidates for these students. In addition to the project work, the student will be given introspective assignments to help crystallize his or her overall experience of the program.

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. Note, this course has proctored exam(s).

This course conveys a high-level vision of programming language theory. It begins with the principles and methodologies of computer programming language such as syntax, semantics, grammar, and parsing. An assortment of programming paradigms is introduced to cover both the traditional imperative and some alternative approaches to program development. These paradigms are presented by the rudiments of a number of representative languages. Note, this course has proctored exam(s).

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. Note, this course has proctored exam(s).

This course covers key knowledge and skills for advanced software development using the object-oriented approach. The student learns, manipulates and reflects on nonlinear data structures such as trees and heaps. Recursive algorithms, sorting algorithms, algorithm efficiency, and advanced design patterns are addressed. To support the advanced concepts and principles of software development, the student will design, code, test, debug, and document programs with increased scale and complexity using industry's best practices (such as GitHub) and the Java programming language. Note, this course has proctored exam(s).

This course covers a broad range of important topics within human computer interaction (HCI) and its implications for the design of interactive systems. By understanding the user?s viewpoint and technology?s effect on people, we can better plan for the selection, design, implementation, and use of technology so that the effects are positive rather than negative. The focus is on the design of interactive systems and human-computer interfaces. The course will cover the current literature and the knowns and unknowns about HCI and design. The design process is centered on the user and is based on a multidisciplinary approach through a synthesis of computer science, cognitive science, and psychology. HCI designers also use analytical and empirical techniques to assess, predict, and evaluate whether a design meets user requirements.

This course reinforces and extends client-server programming concepts to enterprise applications. It introduces Enterprise Java Bean technologies such as JNDI, EJBs and EJB Containers. It explores the current use of XML and XSLT for data representation and communication. The course studies the application of patterns in the design of enterprise architectures. Finally, the course introduces emerging topics related to Web enterprise applications.

In this course we will review the traditional software testing techniques that are applicable to any software product, as well as learn techniques for the paradigm of test-driven development. Continuous delivery and its impact on testing will be discussed. We will also discover how innovative companies are able to build testing and quality into every stage of the development process and deliver a multitude of releases with a relatively small testing organization. We will practice test creation and testing techniques through assignments, individual and group projects. Concepts covered include test cycles; testing objectives; testing in the software development process; types of software errors; reporting and analyzing software errors; problem tracking systems; test case design; testing tools; test planning; test documentation; managing a test group; test-driven development principles; continuous delivery principles and their impact on testing.

A variable content classroom course in Computer Science in which students pursue topics or subjects of current interest that are not part of the regular curriculum. A specific course description will be published online in the Course Schedule for the trimester the course is offered. Note, this course has proctored exam(s).

This course studies the process of designing software systems both from the view of process and from the view of requirements, analysis and the synthesis of a viable software design. It builds on the concepts from the programming sequence to examine the aspects of good design practice.

This course introduces the fundamentals of Business and Data Analytics. Students will learn the fundamentals of business problem framing, data wrangling, descriptive and inferential statistics, data visualization, and data storytelling in analytics. Not open to students with credit for INFA 300.

This course introduces data visualization fundamentals using the leading visualization tools in the industry and focuses on project-based learning. Students will learn how to develop dashboards and discover insight effectively based on data. Not open to students with credit for INFA 350.

Students will learn the basic concepts behind major machine learning algorithms, the essential steps for creating a typical machine learning model, the strengths and weaknesses of different algorithms, and the model evaluation using different performance metrics. Eventually students will be able to build a prediction model by machine learning algorithm using Python language. The differences between Java and Python will be reviewed. The common problems in practical machine learning exercises and their solutions also will be discussed.

In a highly connected, data intensive, and cost-focused business environment, the practice of information security not a business advantage; it is a customer requirement. Viruses, malware, trojans, denial of service attacks, phishing, and even Wiki leaks have become headline news. Failure to insure the confidentiality, integrity, and availability of data costs companies millions, if not billions of dollars in legal settlements, lost business, and trade secrets. In this breadth-based course, you will get an overview of information security principles and practices, including security models, risk management, access controls, intrusion detection and prevention, cryptography, software vulnerabilities, and ethical issues. Subsequent courses expand on this foundational material in much greater depth. Note, this course has proctored exam(s).

Software vulnerabilities, especially those that compromise personal or financial data, are appallingly common. Nearly every major software company has needed to deal with the fallout of a major incident due to vulnerabilities in their products. Writing correct - let alone secure - software is very difficult. Yet users and executives expect it. In this course, you will learn about the typical development mistakes that lead to application-level security issues as well as how to defend against them. Students will explore the Open Web Application Security Project (OWASP) top 10 security vulnerabilities. Topics include unchecked user input, injection, fuzzing, CSRF, XSS, cryptography, CAPTCHA, configuration errors, authentication, and authorization. Note, this course has proctored exam(s).

This course provides a conceptual survey of general systems theory followed by a conceptual and technological survey of the structure of distributed information systems architectures, operating systems, network operating systems, peripheral technology and user interfaces. Interoperability between these architectural components will be explored and current technology and trends in each architectural element will be reviewed. This course will de-emphasize, although not ignore, mainframe architectures in favor of information architectures more applicable to client/server computing. The various interacting categories of client/server computing as well as the benefits and implications of such a system will be fully explored. Note, this course has proctored exam(s).

This course covers the fundamentals of mobile app programming for mobile devices, including smartphones and tablets as well as providing a survey of current mobile platforms, mobile application development environments, and mobile device input and output methods. Students will design and build a variety of Apps throughout the course to reinforce learning and to develop real competency.

This course introduces the principles of analytics modeling. Students will learn exploratory data analytics, regression, classification, clustering, model interpretation, and model evaluation. Not open to students with credit for INFA 420.

This course provides a conceptual survey of general systems theory followed by a conceptual and technological survey of the structure of distributed information systems architectures, operating systems, network operating systems, peripheral technology and user interfaces. Interoperability between these architectural components will be explored and current technology and trends in each architectural element will be reviewed. This course will de-emphasize, although not ignore, mainframe architectures in favor of information architectures more applicable to client/server computing. The various interacting categories of client/server computing as well as the benefits and implications of such a system will be fully explored. Note, this course has proctored exam(s).

This course reinforces and extends client-server programming concepts to enterprise applications. It introduces Enterprise Java Bean technologies such as JNDI, EJBs and EJB Containers. It explores the current use of XML and XSLT for data representation and communication. The course studies the application of patterns in the design of enterprise architectures. Finally, the course introduces emerging topics related to Web enterprise applications.

This course studies the process of designing software systems both from the view of process and from the view of requirements, analysis and the synthesis of a viable software design. It builds on the concepts from the programming sequence to examine the aspects of good design practice.

In this course we will review the traditional software testing techniques that are applicable to any software product, as well as learn techniques for the paradigm of test-driven development. Continuous delivery and its impact on testing will be discussed. We will also discover how innovative companies are able to build testing and quality into every stage of the development process and deliver a multitude of releases with a relatively small testing organization. We will practice test creation and testing techniques through assignments, individual and group projects. Concepts covered include test cycles; testing objectives; testing in the software development process; types of software errors; reporting and analyzing software errors; problem tracking systems; test case design; testing tools; test planning; test documentation; managing a test group; test-driven development principles; continuous delivery principles and their impact on testing.

This course introduces the fundamentals of Business and Data Analytics. Students will learn the fundamentals of business problem framing, data wrangling, descriptive and inferential statistics, data visualization, and data storytelling in analytics. Not open to students with credit for INFA 300.

This course introduces data visualization fundamentals using the leading visualization tools in the industry and focuses on project-based learning. Students will learn how to develop dashboards and discover insight effectively based on data. Not open to students with credit for INFA 350.

Students will learn the basic concepts behind major machine learning algorithms, the essential steps for creating a typical machine learning model, the strengths and weaknesses of different algorithms, and the model evaluation using different performance metrics. Eventually students will be able to build a prediction model by machine learning algorithm using Python language. The differences between Java and Python will be reviewed. The common problems in practical machine learning exercises and their solutions also will be discussed.

This course introduces the principles of analytics modeling. Students will learn exploratory data analytics, regression, classification, clustering, model interpretation, and model evaluation. Not open to students with credit for INFA 420.

This course covers a broad range of important topics within human computer interaction (HCI) and its implications for the design of interactive systems. By understanding the user?s viewpoint and technology?s effect on people, we can better plan for the selection, design, implementation, and use of technology so that the effects are positive rather than negative. The focus is on the design of interactive systems and human-computer interfaces. The course will cover the current literature and the knowns and unknowns about HCI and design. The design process is centered on the user and is based on a multidisciplinary approach through a synthesis of computer science, cognitive science, and psychology. HCI designers also use analytical and empirical techniques to assess, predict, and evaluate whether a design meets user requirements.

This course covers the fundamentals of mobile app programming for mobile devices, including smartphones and tablets as well as providing a survey of current mobile platforms, mobile application development environments, and mobile device input and output methods. Students will design and build a variety of Apps throughout the course to reinforce learning and to develop real competency.

This course studies the process of designing software systems both from the view of process and from the view of requirements, analysis and the synthesis of a viable software design. It builds on the concepts from the programming sequence to examine the aspects of good design practice.

In this course we will review the traditional software testing techniques that are applicable to any software product, as well as learn techniques for the paradigm of test-driven development. Continuous delivery and its impact on testing will be discussed. We will also discover how innovative companies are able to build testing and quality into every stage of the development process and deliver a multitude of releases with a relatively small testing organization. We will practice test creation and testing techniques through assignments, individual and group projects. Concepts covered include test cycles; testing objectives; testing in the software development process; types of software errors; reporting and analyzing software errors; problem tracking systems; test case design; testing tools; test planning; test documentation; managing a test group; test-driven development principles; continuous delivery principles and their impact on testing.

This course provides a conceptual survey of general systems theory followed by a conceptual and technological survey of the structure of distributed information systems architectures, operating systems, network operating systems, peripheral technology and user interfaces. Interoperability between these architectural components will be explored and current technology and trends in each architectural element will be reviewed. This course will de-emphasize, although not ignore, mainframe architectures in favor of information architectures more applicable to client/server computing. The various interacting categories of client/server computing as well as the benefits and implications of such a system will be fully explored. Note, this course has proctored exam(s).

In a highly connected, data intensive, and cost-focused business environment, the practice of information security not a business advantage; it is a customer requirement. Viruses, malware, trojans, denial of service attacks, phishing, and even Wiki leaks have become headline news. Failure to insure the confidentiality, integrity, and availability of data costs companies millions, if not billions of dollars in legal settlements, lost business, and trade secrets. In this breadth-based course, you will get an overview of information security principles and practices, including security models, risk management, access controls, intrusion detection and prevention, cryptography, software vulnerabilities, and ethical issues. Subsequent courses expand on this foundational material in much greater depth. Note, this course has proctored exam(s).

Software vulnerabilities, especially those that compromise personal or financial data, are appallingly common. Nearly every major software company has needed to deal with the fallout of a major incident due to vulnerabilities in their products. Writing correct - let alone secure - software is very difficult. Yet users and executives expect it. In this course, you will learn about the typical development mistakes that lead to application-level security issues as well as how to defend against them. Students will explore the Open Web Application Security Project (OWASP) top 10 security vulnerabilities. Topics include unchecked user input, injection, fuzzing, CSRF, XSS, cryptography, CAPTCHA, configuration errors, authentication, and authorization. Note, this course has proctored exam(s).

In this course we will review the traditional software testing techniques that are applicable to any software product, as well as learn techniques for the paradigm of test-driven development. Continuous delivery and its impact on testing will be discussed. We will also discover how innovative companies are able to build testing and quality into every stage of the development process and deliver a multitude of releases with a relatively small testing organization. We will practice test creation and testing techniques through assignments, individual and group projects. Concepts covered include test cycles; testing objectives; testing in the software development process; types of software errors; reporting and analyzing software errors; problem tracking systems; test case design; testing tools; test planning; test documentation; managing a test group; test-driven development principles; continuous delivery principles and their impact on testing.