Online Bachelor’s in Computer Science Curriculum

This course covers data types, statements, expressions, control flow, functions, object oriented programming. It emphasizes principals of software development, debugging and testing. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course introduces students to fundamental features of Java programming language. Topics include data types, control flow and loops, objects, classes, encapsulation, inheritance and polymorphism.

This is an introduction to computer programming in C++ language. The course covers structural programming concepts, simple data types and algorithms in addition to basic C++ syntax, operators, control structures, arrays, pointers, function parameter passing, and object programming. Projects are required for coding techniques, program design, and debugging.

This course covers the practical application and usage of database systems. An emphasis is placed on relational databases, but non-relational databases are introduced as well. Topics include database design and architecture, the SQL language, data storage, database programming, and NoSQL databases. Prerequisite: COSC 130, COSC 150, or DSCI 303

This course covers the project management methodologies. Topics covered include: project planning, quality management, time and cost management, agile, waterfall and risk management.

This course studies the design and implementation of data structure and algorithms. Topics include applications of data structures such as stacks, queues and linked-lists, analysis of algorithms, and algorithmic tools and techniques, including sorting and searching methods. Requires substantial object programming projects to solve real world problems using these data structure and algorithms.

Exposure to Windows, Linux, and Unix Operating systems. The course covers the theoretical aspects of operating systems including system structures, scheduling, threads and concurrent processes, deadlock detection and prevention, storage and file management, virtual memory, system protection and security.

This course is the final course of the computer science program. This capstone course provides an opportunity to apply the knowledge and skills gained from the program to solve real-world problems. Taken as the last course of the program .Prerequisite: Senior Status and Computing Core

This course covers data types, statements, expressions, control flow, top Python core libraries (NumPy, SciPy, Pandas, Matplotlib and Seaborn) and modeling libraries (Statsmodels and Scikit-learn). Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. Cross-Listed: DSCI-503

This is an introductory course in machine learning intended primarily for students majoring or minoring in Mathematics, Data Science or Actuarial Science. This course may also be useful for those using predictive modeling techniques in business, economics or research applications. The main focus of this course is to understand the basic operations and applications of what we currently call machine learning. This course will cover material from several sources. A few main topics that will be covered include: how machine learning differs from traditional programming techniques, data manipulation and analysis, some basic coding skills and an introduction to some of the tools available for data scientists. Specific application techniques will include the following (as time permits): data acquisition, classification, regression, overfitting, supervised and unsupervised training, normalization, distance metrics, k-means clustering, error calculation, optimization training, tree-based algorithms (including random forests), frequent item sets and recommender systems, sentiment analysis, neural networks, genetic algorithms, visualizations, and deep learning (including an introduction to convolutional neural networks and generative adversarial networks). Cross-Listed: DSCI-508

This course is an introduction to deep learning with an emphasis on the development and application of advanced neural networks. It covers convolutional neural networks, recurrent neural networks, generative adversarial networks, and deep reinforcement learning. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course provides an introduction to the field of Artificial Intelligence. Topics covered may include, but are not limited to: History of Artificial Intelligence, logic, game theory, search algorithms, knowledge representation, and automated planning. Prerequisite: DSCI 303

This course covers introduction to robotics, applications of robots, return-on-investment, abstract models, controlling robot motion, complex motion, robotic sensors, input/output, external sensors, threads, event programming, remote communication, remote sensing, behavior programming, and human/robot interfaces. Students will gain hands-on experience with emerging robot technologies, understand industrial applications of robots, and ramifications of human/robot interaction.

This course provides students with an introduction to the theory and practice of computer vision - the practice of analyzing visual images from the world. This course will cover a wide range of computer techniques and problems that address "how we make computers see".

This course provides an introduction to the field of Reinforcement Learning with an emphasis on Deep Reinforcement Learning. Topics cover may include, but are not limited to: Markov decision processes, value-based methods, Deep Q-networks, policy-gradient methods, actor-critic algorithms, and multi-agent problems.

This course introduces students to a range of potential ethical issues related to the current and future use of artificial intelligence. Topics discussed will include the role of artificial intelligence in society, as well as the use of artificial intelligence in areas such as manufacturing, finance, healthcare, government, and law enforcement.

This course is a survey of some of the current and possible future applications of artificial intelligence. The course will explore applications in fields such as business, transportation, manufacturing, healthcare, cybersecurity, and geospatial analysis.

This course covers text analytics, the practice of extracting useful information hidden in unstructured text such as social media, emails and web pages using Python. Topics include working with corpora, transformations, metadata management, term document matrices, word clouds, and topic models. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course provides a foundational understanding of blockchain to students. The idea of what blockchain is, why it is needed, and the problems it solves is covered. An overview of how blockchain technology works and is developed is covered as well as the structure of these technologies. The potential as well as the limitations of blockchain is reviewed as well as how these limitations can be overcome.

This course presents students an understanding of the different types of blockchain networks including but not limited public, private, consortium, and permissioned networks. The user of blockchain networks and the value that can be brought to businesses, industry sectors, and society are explored.

This course explores the basic properties of various cryptocurrencies (e.g bitcoin, ethereum, ether). Cryptography techniques will be explored to gain a fundamental understanding of the mechanics behind cryptocurrencies.

This course explores the ethical and legal hurdles and consequences of implementing blockchain technologies. Analyzing historical and contemporary case studies, this course allows for an exploration of blockchain across industries for the implementation and scaling of blockchain technology. Current events involving blockchain in the legal system, corporate world, and the public sphere will be addressed and examined.

This course allows students to put into practice blockchain principles with the development of a blockchain application. This course also covers the different uses of blockchain across industries including cryptocurrencies, smart contracts, and ledgers.

This course explores the ethical and legal hurdles and consequences of implementing blockchain technologies. Analyzing historical and contemporary case studies, this course allows for an exploration of blockchain across industries for the implementation and scaling of blockchain technology. Current events involving blockchain in the legal system, corporate world, and the public sphere will be addressed and examined.

This course will allow students to implement and audit the Critical Security Controls as documented by the Council on Cyber Security. These Critical Security Controls are rapidly becoming accepted as the highest priority list of what must be done and proven at nearly all organizations.

This course will involve assessing target networks and hosts for security vulnerabilities. Specific penetration testing and ethical hacking methodologies will be discussed and used on network devices, client machines, and mobile devices.

This course will examine both network device security and wireless security issues. For wireless security, specific attention will be paid on WiFi and Bluetooth technologies.

Virtualization technologies require planning with regard to access controls, user permissions and traditional security controls. Virtualized infrastructure is being located in the cloud which will dictate policies and processes that will need to be adapted to work within a cloud structure.

This course will focus on digital forensic practices, tools, and exercises for the collection of electronic evidence on network, client, and mobile devices. Specific discussion will also include the introduction process of this electronic evidence in civil and criminal cases.

This course explores malware analysis tools and techniques that target and infect Windows systems. Knowing the capabilities of malware is critical to an organization’s ability to derive threat intelligence, respond to information security incidents, and establish defenses.

This course covers data types, statements, expressions, control flow, top Python core libraries (NumPy, SciPy, Pandas, Matplotlib and Seaborn) and modeling libraries (Statsmodels and Scikit-learn). Project based learning is used to help students develop effective problem solving skills and effective collaboration skills. Cross-Listed: DSCI-503

This is an introductory course in machine learning intended primarily for students majoring or minoring in Mathematics, Data Science or Actuarial Science. This course may also be useful for those using predictive modeling techniques in business, economics or research applications. The main focus of this course is to understand the basic operations and applications of what we currently call machine learning. This course will cover material from several sources. A few main topics that will be covered include: how machine learning differs from traditional programming techniques, data manipulation and analysis, some basic coding skills and an introduction to some of the tools available for data scientists. Specific application techniques will include the following (as time permits): data acquisition, classification, regression, overfitting, supervised and unsupervised training, normalization, distance metrics, k-means clustering, error calculation, optimization training, tree-based algorithms (including random forests), frequent item sets and recommender systems, sentiment analysis, neural networks, genetic algorithms, visualizations, and deep learning (including an introduction to convolutional neural networks and generative adversarial networks). Cross-Listed: DSCI-508

This course targets data scientists and engineers. It covers programming with RDDS, Tuning and debugging Spark, Spark SQL, Spark steaming and machine learning with MLlib. It provides students the tools to quickly tackle big data analysis problems on one machine or hundreds. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course covers practical issues in data analysis and graphics such as programming in R, debugging R code, Jupyter Notebook, cloud computing, data exploration, and data visualization. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course is for students who want to enhance their SQL skills through exploring real-world examples. Topics covered include but are not limited to pattern-matching using regular expressions, analytical functions, and common table expressions. Students are expected to be able to construct advanced SQL queries to retrieve desired information from the database and solve real-world problems Cross-listed: DSCI-504

This course covers text analytics, the practice of extracting useful information hidden in unstructured text such as social media, emails and web pages using Python. Topics include working with corpora, transformations, metadata management, term document matrices, word clouds, and topic models. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course is an introduction to deep learning with an emphasis on the development and application of advanced neural networks. It covers convolutional neural networks, recurrent neural networks, generative adversarial networks, and deep reinforcement learning. Project based learning is used to help students develop effective problem solving skills and effective collaboration skills.

This course is a survey of both computer systems and programming languages. It covers the current state of systems as well as the top programming languages in use today. Theoretical and practical application of different programming language styles are used to help students understand the effective use cases for them.

In this course, students conduct an in-depth exploration of the entire software development process. This includes the technology business hierarchy and structure as well as different software development methodologies. An analysis of major stakeholders and their roles and responsibilities is addressed.

This course will explore the development of robust web applications across the internet. Students will develop web applications in HTML, CSS, and Javascript and learn how to build and maintain web applications effectively and efficiently.

This course explores the process steps of object-oriented analysis and design.  Using real-world application and problem sets, students explore software requirements and design principles used to make great software.

In this course, students will apply their experience with database management and software to deploy and manage a fully realized web-based application in the cloud. Students will complete and automate the production and deployment of the system.

This course explores emerging and relevant trends in technology. Students explore the application of these trends as well as their development standards and processes. Students also understand the technology acceptance cycle with an emphasis on spotting future trends as they evolve.

The movement of more and more information to mobile applications and technology has changed the human perspective of the world and our interactions with each other. Understanding the design of apps and how to root them in real world problems becomes an exercise. However, despite the new technology, foundational principles of design are held as a way to continuously improve on the design to produce a more engaging and effective experience. Storyboarding is a visual way of developing an application’s user interface prior to undergoing any development activities. Coupled with sketching, mockups, and prototypes, a person building an application can test and refine their ideas using less time and effort. This course serves as an introduction to the technique of storyboarding, including organizing a project’s content and arranging it in a visual format utilizing standard tools while holding to fundamental design principles in terms of color, layout, and typography. This course also aims to illustrate the benefits, consequences, and changes that have occurred and continue to occur as technology becomes more integrated in our lives.

This course begins the student understanding of the programming language Swift in order to develop iOS mobile applications as well as continuing to understand the impact that technology has on modern society. Students will develop iOS apps in the context of the XCode integrated development environment (IDE) while building experience with the vocabulary and app design patterns supported by XCode and its suite of tools.

An introduction to vector and raster graphics, page layout software, and the general tools and technologies of graphic design. Students will explore and apply fundamental principles of art and design utilizing industry standard software (Adobe Suite). This course requires no previous computer experience.

An introduction to the practice, language, and purpose of graphic design. Through completing a variety of projects, students explore and apply the elements and principles of visual communication in pursuit of crafting their creative process, understanding theory and practice, and refining visual and technical skills.

This course introduces students to the visual, theoretical, and technical considerations of designing desktop and mobile websites. Its focus is on producing interactive prototypes using industry-standard software and pursuing an introductory understanding of principles, processes, and practices specific to user experience and interface design. For context, this course also introduces students to basic HTML and CSS. Prerequisite: ADGD 260 or ADDM 200

This course’s purpose is to advance students’ understanding of the specialized disciplines, user experience and user interface design. Students will pursue advancing visual and interactive communication skill sets as they complete application focused projects that seek to create effective user experiences. Focus is placed on principles, processes, and practices specific to user experience and user interface design and include topics such as usability, user interaction, iconography, mapping, and prototyping.