Computer Science

This course provides an introduction to the field of computer science. Topics to be covered include: basics of computer architecture and organization, digital logic and data representation, algorithm analysis and design, programming languages, and software engineering.

Fall
This course provides an introduction to the principles and practices of software engineering. It is designed to serve as a first course in computer science for students and introduce students to software engineering practices.

Students will learn about the software development life cycle, including requirements analysis, system design, coding, testing, and maintenance. The course will also cover project management techniques and tools, software quality assurance, and the ethical and professional responsibilities of a software engineer.

A practical orientation to modern version control systems and collaborative software development practices. Students learn to use Git for tracking changes, branching, and merging code. Topics include repository management, branching strategies, pull requests, code review, GitHub/GitLab platform workflows, and the fundamentals.

Fall
This course introduces the student to the process of creating algorithms for the solution of problems using a computer.  Problem solving structures will first be presented independent of programming language.  Concepts, including variables, assignment statements, conditionals, loops, functions, and arrays are explored.

This course provides a foundational understanding of machine learning concepts, algorithms, and practical implementation. Students explore supervised and unsupervised learning techniques including regression, classification, and clustering. Topics involve the use of industry-standard frameworks such as scikit-learn. Hands-on projects using real-world datasets reinforce theoretical concepts throughout the course.

This course is designed to provide the student with the knowledge and ability to design, build, consume, and deploy modern web services. Students explore RESTful API design principles, cloud computing fundamentals across major platforms (AWS, Azure, and GCP), containerization with Docker, and application deployment strategies.

Spring
This course will provide an in-depth exploration of Object-Oriented Programming as well as advanced concepts in programming.  Included are the topics of classes and subclasses, encapsulation, inheritance, polymorphism, event handling, exception handling, and garbage collection.

Fall
This course is a comparative survey of programming languages and their paradigms that includes examinations of the properties, applications, syntax, and semantics of selected programming languages.  Students will be expected to have a solid programming background such that they can quickly learn various aspects of different programming languages on their own.

Spring
This course will cover recursion, linked lists, stacks, queues, hashing, graphs, and trees, as well as strategies for choosing the right data structure.  Also presented will be divide-and-conquer strategies, sorting algorithms, and analysis of algorithms.

Spring
This course will explore computer organization and architecture.  Topics covered will include: computer architecture, computer organization, number systems, storage concepts, I/O, memory management, and process management.  Assembly language will be used. 

This course supports a critical thinking approach to develop the skills with cleaning messy data, transforming datasets, exploratory data analysis, and building visualizations with tools like pandas, matplotlib, and Jupyter notebooks. The ability to prepare and interpret data is basic need for anyone working alongside AI systems.

A semester-long team project that integrates software engineering practices, AI
tools, database work, and deployment into a real deliverable. Students define
requirements, build the product, document it, present it, and reflect on the process.
Industry mentors or community partners provide real-world context.