Accelerated Computer Science Bachelor's and Master's Degree

Operating Systems for Computer Scientists focuses on the intricacies of operating systems. This comprehensive course for computer science students covers core principles such as processes, threads, memory management, and file systems, providing students with insights into CPU scheduling algorithms, deadlock handling, and system performance optimization. Additionally, the course delves into security mechanisms, addressing common threats and preventative measures. Through a blend of theoretical concepts and practical applications, students emerge equipped to adeptly navigate operating system features and prepared for real-world challenges in computer science.

This course builds on foundational knowledge of algorithm design and optimization for efficient resource utilization. It emphasizes benchmarking algorithms, reasoning, and applying Big O notation for performance evaluation. This course will cover how to design, analyze, and implement algorithms to solve complex computational problems, focusing on optimizing performance and enhancing system efficiency. The practical applications in this course involve testing data structures, developing algorithmic solutions, and optimizing algorithm performance through critical analysis and implementation. By integrating computational thinking and engineering principles, this course will present the skills students need to develop and optimize algorithms for real-world software, using benchmarking and profiling tools to measure and enhance performance.

Data Structures and Algorithms II explores the analysis and implementation of high-performance data structures and supporting algorithms, including graphs, hashing, self-adjusting data structures, set representations, and dynamic programming. The course also introduces students to NP-complete problems. The course discusses how to use Python techniques to implement software solutions for problems of memory management and data compression. This course has two prerequisites: Data Structures and Algorithms I and Discrete Math II.

Introduction to AI for Computer Scientists provides an overview of critical terminology and key concepts for artificial intelligence (AI). The course explores the history and evolution of AI, elements of code, and the process for understanding algorithmic approaches to AI. The course presents topics of bias, ethical issues, and security concerns. Contextualized examples offer students an opportunity to see these concepts in professional scenarios; identifying issues within code, understanding the steps within an AI design, and understanding the different features, limitations, and benefits for a multitude of AI applications.

Artificial Intelligence Optimization for Computer Scientists guides students through the implementation and optimization of artificial intelligence (AI) solutions for various applications. Through extensive research, students will explore different AI approaches and determine the most applicable solutions for specific scenarios. Practical, hands-on exercises will enable students to implement and rigorously test AI solutions, thus honing their skills in optimizing AI models for enhanced performance and efficiency. Additionally, this course delves into creating data assumptions and interpretations that are crucial for predictive analytics and future data forecasting. Finally, students will adapt and extend AI solutions to address diverse application scenarios, ensuring their readiness to tackle real-world challenges in AI optimization and deployment. Introduction to Artificial Intelligence for Computer Scientists is a prerequisite to this course.

Artificial Intelligence and Machine Learning Foundations explores foundational concepts and practical applications of artificial intelligence (AI) and machine learning (ML). It provides students with an understanding of the historical context and evolution of AI and the subsequent growth phases of AI technologies. This course will investigate the computational theories and logical frameworks that have shaped the AI landscape, examining how advancements in hardware have enabled the leap from basic ML to the complexities of deep learning. The course emphasizes the practicalities of AI and ML and gives insights into the critical role of data integrity and the techniques for data wrangling to feed into ML algorithms effectively. In addition to the technical skills, the course incorporates the societal implications of AI and ML, discussing current ethical considerations. This course aims to create a nuanced understanding of AI and ML, preparing students to thoughtfully consider the broader impacts of these technologies. There are no prerequisites for this course.

Computer Science Project Development with a Team has students prepare a prior project for submission to a mock technical and executive leadership team. This course expands on the coding work done in a previous course, asking students to submit three artifacts. The final artifact is a business proposal aimed at convincing stakeholders to implement the project, which includes an executive summary of product requirements directed at the IT audience, as well as a technical report of the fully functional data product intended to solve a real-world problem. Artifacts are evaluated by peer team members prior to submission, and students practice giving, receiving, and integrating feedback into their work process.

Computer Architecture introduces students to concepts and characteristics of organization and architecture applied to modern computer systems including performance, processor, memory, input/output, and multiprocessors to optimize system design, performance, and efficiency.

Introduction to Computer Science introduces learners to the field of computer science and its essential concepts. In this course students will explore, among other topics, programming basics through language-agnostic pseudocode, computational thinking and problem-solving, algorithms, hardware, and social and ethical considerations in the field. This course is designed for beginners to gain a solid understanding of computer science principles and their applications and prepare students for further study in the field. There are no prerequisites for this course.

Formal Languages Overview introduces students to programming language design and theory, focusing on formal semantics and type systems. It covers imperative, functional, and parallel languages, emphasizing techniques for proving language properties and verifying program specifications. Students will differentiate between functional and procedural languages, and explore compiled, interpreted, query, and assembly languages. The course also examines the structure and features of programming languages, including object-oriented programming principles. Learners will understand program correctness, testing, and verification, addressing type correctness. This course prepares students to assess programming languages against business requirements, enhancing software reliability and efficiency. Aimed at those interested in the theoretical underpinnings of programming languages, it equips students with knowledge to make informed decisions in software development and application.

The Practical Applications of Prompt course introduces learners to generative artificial intelligence (AI). This course aims to allow learners to gain skills for writing effective prompts and develop more effective conversations with artificial intelligence. Practical Applications of Prompt will lead learners to explore why prompt engineering is necessary. The course also aims to help learners, regardless of background, increase prompt fluency, which is fluency in using prompt effectively. The course teaches learners how to create effective prompts to elicit information with consideration of scope, specificity, and context; additionally, it teaches learners to evaluate the medium of the prompt and adjust prompts to output relevant results. The last section of the course focuses on ways to evaluate the efficacy of prompts and improve the depth and quality of analytical investigations. This approach prepares students to navigate the complexities of working with generative AI and use these skills effectively throughout their careers.

Advanced Java refines object-oriented programming expertise and skills. You will implement multithreaded, object-oriented code with the features of Java necessary to develop software that meets business requirements. Additionally, you will determine how to deploy software applications using cloud services. This course requires intermediate expertise in object-oriented programming and the Java language.

Back-End Programming introduces students to creating back-end components of a web application with the support of framework packages. This course also teaches students how to implement database functionality in a web application and how to create web services. This course requires intermediate expertise in object-oriented programming and the Java language.

Java Fundamentals introduces you to object-oriented programming in the Java language. You will create and call methods, design Java classes, and other object-oriented principles and constructs to develop software that meets business requirements. This course requires foundational knowledge of programming including variables, type, program flow and debugging.

In this undergraduate course students explore the various aspects of the C++ programming language by examining its syntax, the development environment, and tools and techniques to solve some real-world problems.

Java Frameworks builds object-oriented programming expertise and introduces powerful new tools for Java application development. Students will execute exception handling, Java frameworks, and other object-oriented principles and constructs to develop a complete application including a user interface. This course requires foundational knowledge of object-oriented programming and the Java language.

Software Design and Quality Assurance applies a QA focus to every phase of the software development life cycle. This course investigates best practices for quality analysis, quality planning, and testing strategies as they pertain to the everyday practice of software development. Students will come to understand how their work fits into the bigger picture: how QA, testing, and code-writing practices interact within specific process models; the potential impact of new code on existing code or on other applications; the importance of usability and the influence users have on the ultimate success of an application. Students will explore test plans, test cases, unit tests, integration tests, regression tests, usability tests, and test and review tools.

Business of IT - Applications examines Information Technology Infrastructure Library (ITIL®) terminology, structure, policies, and concepts. Focusing on the management of information technology (IT) infrastructure, development, and operations, learners will explore the core principles of ITIL practices for service management to prepare them for careers as IT professionals, business managers, and business process owners. This course has no prerequisites.

Software Engineering introduces the concepts of software engineering to students who have completed the core courses in programming and project management. The principles build on previously acquired concepts, switching the emphasis from programming simple routines to engineering robust and scalable software solutions. This course does not cover programming, but it provides an overview of software engineering processes and their challenging nature, focusing on the need for a disciplined approach to software engineering. A generic process framework provides the groundwork for formal process models. Prescriptive process models such as the Waterfall Model and Agile Development are included. This course also introduces the elements and phases of software engineering, including requirements engineering, design concepts, and software quality. There are no prerequisites for this course.

Network and Security - Foundations introduces learners to the basic network systems and concepts related to networking technologies. Learners will gain skills in applying network security concepts for business continuity, data access, and confidentiality, and in identifying solutions for compliance with security guidance.

Ethics in Technology examines the ethical considerations of technology use in the 21st century and introduces students to a decision-making process informed by ethical frameworks. Students will study specific cases related to important topics such as surveillance, social media, hacking, data manipulation, plagiarism and piracy, artificial intelligence, responsible innovation, and the digital divide. This course has no prerequisites.

Health, Fitness, and Wellness focuses on the importance and foundations of good health and physical fitness—particularly for children and adolescents—addressing health, nutrition, fitness, and substance use and abuse.

Discrete Mathematics I helps candidates develop competence in the use of abstract, discrete structures fundamental to computer science. In particular, this course will introduce candidates to logic and proofs; Boolean algebra and functions; set theory; finite and infinite sequences and series; and relations, graphs, and trees. The course emphasizes applications in computer science. Calculus I is a prerequisite for this course.

Welcome to Introduction to Communication: Connecting with Others! It may seem like common knowledge that communication skills are important, and that communicating with others is inescapable in our everyday lives. While this may appear simplistic, the study of communication is actually complex, dynamic, and multifaceted. Strong communication skills are invaluable to strengthening a multitude of aspects of life. Specifically, this course will focus on communication in the professional setting, and present material from multiple vantage points, including communicating with others in a variety of contexts, across situations, and with diverse populations. Upon completion, you will have a deeper understanding of both your own and others’ communication behaviors, and a toolbox of effective behaviors to enhance your experience in the workplace.

This course provides students an introduction to using the scientific method and engaging in scientific research to reach conclusions about the natural world. Students will design and carry out an experiment to investigate a hypothesis by gathering quantitative data. They will also research a specific ecosystem using academic sources and draw conclusions from their findings.

Discrete Mathematics II addresses abstract, discrete, computational methods used in computer science. In particular, this class introduces searching and sorting algorithms; big-O estimates; number theory and cryptography; recursion and induction; counting and advanced counting techniques; discrete probability; and modeling computation. This course emphasizes applications in computer science. Discrete Mathematics I is a prerequisite for this course.

Welcome to Composition: Successful Self-Expression! In this course, you will focus on four main topics: professional writing for a cross-cultural audience, narrowing research topics and questions, researching for content to support a topic, and referencing research sources. Each section includes learning opportunities through readings, videos, audio, and other relevant resources. Assessment activities with feedback also provide opportunities to check your learning, practice, and show how well you understand course content. Because the course is self-paced, you may move through the material as quickly or as slowly as you need to gain proficiency in the seven competencies that will be covered in the final assessment. If you have no prior knowledge or experience, you can expect to spend 30-40 hours on the course content. You will demonstrate competency through a performance assessment. There is no prerequisite for this course and there is no specific technical knowledge needed.

American Politics and the U.S. Constitution examines the evolution of representative government in the United States and the changing interpretations of the civil rights and civil liberties protected by the Constitution. This course will give candidates an understanding of the powers of the branches of the federal government, the continual tensions inherent in a federal system, the shifting relationship between state and federal governments, and the interactions between elected officials and the ever-changing electorate. This course will focus on such topics as the role of a free press in a democracy, the impact of changing demographics on American politics, and the debates over and expansion of civil rights. Upon completion of the course, candidates should be able to explain the basic functions of the federal government, describe the forces that shape American policy and politics, and be better prepared to participate in America’s civic institutions. This course has no prerequisite.

Applied Probability and Statistics is designed to help students develop competence in the fundamental concepts of basic statistics including: introductory algebra and graphing; descriptive statistics; regression and correlation; and probability. Statistical data and probability are often used in everyday life, science, business, information technology, and educational settings to make informed decisions about the validity of studies and the effect of data on decisions. This course discusses what constitutes sound research design and how to appropriately model phenomena using statistical data. Additionally, the content covers simple probability calculations, based on events that occur in the business and IT industries. No prerequisites are required for this course.

This course guides candidates to apply theoretical concepts of calculus to real-world situations, demonstrating a developing mathematical mindset. This course focuses on limits, derivatives, integrals, and differential equations; it also prepares students for Discrete Mathematics. Prerequisites may include an entrance exam that assesses pre-calculus skills, or readiness; alternatively, completion of pre-calculus within the past 3 – 5 years.

Introduction to Systems Thinking and Applications provides learners with the skills required to engage in a holistic systems-based approach to analyzing complex problems and solutions. This course introduces the foundational concepts and principles of systems thinking and provides opportunities to use a systems thinking approach to analyze and evaluate real-world case studies. The course will culminate with using systems thinking to develop a solution to an authentic complex problem. This course has no prerequisites, but general education math (C955 or C957) is preferred. Because the course is self-paced, learners may move through the material as quickly or as slowly as needed, with the goal of demonstrating proficiency in the five competencies covered in the final assessment. If learners have no prior knowledge of this material, they can expect to spend 30 to 40 hours on the course content.

Web Development Foundations introduces students to web design and development using HTML, XML, and Cascading Style Sheets (CSS), the foundational languages of the web. This course also covers how to troubleshoot problems using developer tools and integrated development environments commonly employed in web development. There are no prerequisites for this course. 

Linux Foundations prepares learners for the LPI Linux Essentials certification, and is an introduction to Linux as an operating system as well as an introduction to open-source concepts and the basics of the Linux command line. Learners will gain skills in identifying the fundamentals of open-source software and to develop resources for data access and security.

This course lays the foundation for understanding terminology, principles, processes, and best practices of information security at local and global levels. It further provides an overview of basic security vulnerabilities and countermeasures for protecting information assets through planning and administrative controls within an organization. This course has no prerequisites.

Version control is critical to maintaining software and enabling scalability solutions. A best practice for any programming project that requires multiple files uses version control. Version control enables teams to have collaborative workflows and enhances the software development lifecycle. This course introduces students to the basics of publishing, retrieving, branching, and cloning. There are no prerequisites for this course.

Data Management Foundations offers an introduction in creating conceptual, logical and physical data models.  Students gain skills in creating databases and tables in SQL-enabled database management systems, as well as skills in normalizing databases. No prerequisites are required for this course

Data Management - Applications covers conceptual data modeling and introduces MySQL. Students will learn how to create simple to complex SELECT queries, including subqueries and joins, and how to use SQL to update and delete data. Topics covered in this course include exposure to MySQL; creating and modifying databases, tables, views, foreign keys and primary keys (FKs and PKs), and indexes; populating tables; and developing simple Select-From-Where (SFW) queries to complex 3+ table join queries. The following course is a prerequisite: Data Management - Foundations.