Undergraduate Catalog

●   Build and style websites using HTML and CSS

●   Apply foundational JavaScript to create interactive web content

●   Use logic and pseudocode to design programmatic solutions to real-world problems

●   Plan, build, and present a web-based project for a non-technical audience

●   Write JavaScript for both browser-based and command-line environments

●   Implement interactivity using DOM manipulation, asynchronous programming, and web APIs

●   Build and present a front-end project designed for public communication and clarity

●   Collaborate with peers to review code and improve usability

●   Build reusable user interface components using React

●   Manage front-end state and API-driven data using asynchronous JavaScript

●   Apply accessibility and responsive design principles to front-end development

●   Use modern development tooling, including version control, linters, and build tools

●   Translate wireframes and mockups into fully functional component-based layouts

●   Write Python programs using variables, expressions, loops, and functions

●   Apply algorithmic thinking and decomposition to solve structured programming challenges

●   Manipulate core data structures, including strings, lists, dictionaries, and tuples

●   Build a command-line application to perform real-world data tasks

●   Model and implement complex data relationships using classes and objects in Python

●   Apply abstraction and encapsulation to design modular, reusable code

●   Create and document RESTful APIs using industry-standard Python frameworks

●   Retrieve and process JSON data from web services

●   Build reusable, testable backend components

●   Write SQL queries to create, read, update, and delete data from relational databases

●   Connect APIs to relational databases using Python and an ORM

●   Design and build secure RESTful APIs with user authentication using Flask

●   Apply best practices in code quality, including documentation, validation, and unit testing

●   Discuss ethical considerations in data access, privacy, and system integrity

●   Build and deploy a web application as part of a collaborative software team

●   Apply project management practices using the SCRUM framework, including sprints, reviews, and retrospectives

●   Rotate through team roles, including Scrum master, product owner, and technical lead

●   Conduct code reviews and use modern technical collaboration tools

●   Communicate technical decisions to both technical and non-technical audiences

●   Implement and analyze core linear data structures, including linked lists, arrays, stacks, and queues

●   Build these structures from scratch and represent algorithms using pseudocode

●   Apply algorithms to real-life problems to understand complexity and performance tradeoffs

●   Practice solving technical interview problems and communicating solutions clearly

●   Implement and analyze advanced data structures, including priority queues, hash tables, and binary search trees

●   Build and apply graph algorithms to problems in maps, social networks, and real-world applications

●   Apply divide and conquer recursion, greedy algorithms, and dynamic programming techniques

●   Solve common algorithmic problems found in technical interview settings

●   Communicate technical solutions through structured writing and verbal explanation

●   Identify core hardware components and describe how they interact within a computing system

●   Operate and configure virtual machines for secure testing environments

●   Execute basic Linux and Windows commands for system exploration and administration

●   Identify built-in operating system security tools and explain their role in protecting systems

●   Analyze and interpret computer network diagrams to understand system architecture and data flow

●   Configure and manage virtualized Linux and Windows environments

●   Execute advanced Linux commands to automate system management and enforce security controls

●   Identify and mitigate common vulnerabilities in enterprise systems, including Active Directory environments

●   Secure cloud-based resources using best practices in identity management, encryption, and configuration

●   Explain the role and lifecycle of cyber threat intelligence in organizational security

●   Apply the MITRE ATT&CK framework to analyze adversarial behavior and inform defense strategies

●   Use SIEM tools to collect, correlate, and analyze logs for real-time threat detection

●   Conduct structured threat hunts based on Indicators of Compromise and known attack patterns

●   Execute vulnerability scans and interpret findings to prioritize remediation

●   Assess IT infrastructure for architectural vulnerabilities using industry-standard frameworks

●   Apply principles of secure design to mitigate risk in traditional, cloud, and hybrid environments

●   Use PySpark to process and analyze large-scale structured and semi-structured datasets in cloud environments

●   Build data pipelines integrating SQL and Python tools across cloud platforms

●   Create interactive dashboards to communicate data insights

●   Investigate and respond to cybersecurity incidents using digital forensics best practices

●   Analyze malware behavior across Windows and Linux systems

●   Conduct structured penetration testing using reconnaissance, scanning, and exploitation tools

●   Use industry tools, including Metasploit, Burp Suite, and Nmap to conduct ethical attacks

●   Document and present vulnerability findings and remediation recommendations

●   Analyze real-world datasets using statistical and programmatic methods in Python

●   Create and interpret data visualizations using Seaborn and Matplotlib

●   Apply object-oriented programming to structure and clean data

●   Communicate insights through structured reports and visual storytelling

●   Discuss ethical considerations surrounding data privacy, sharing, and algorithmic decision-making

●   Apply core inferential statistics techniques to analyze real-world datasets

●   Conduct hypothesis testing for single and multiple group comparisons

●   Implement simple and multiple linear regression models to analyze relationships between variables

●   Apply diagnostic techniques to assess and improve regression model performance

●   Use PySpark and Python to process and analyze large datasets at scale

●   Implement supervised learning models, including logistic regression, decision trees, and support vector machines

●   Apply unsupervised learning methods such as k-means and PCA for clustering and dimensionality reduction

●   Preprocess data and apply feature engineering techniques to prepare datasets for modeling

●   Evaluate model performance using appropriate metrics, including accuracy, precision, and ROC AUC

●   Communicate model findings and trade-offs clearly to technical and non-technical audiences

●   Apply natural language processing techniques to tasks such as text classification and vectorization

●   Implement and train neural network architectures, including CNNs, RNNs, and Transformers

●   Build and optimize deep learning models for real-world AI applications

●   Manage and analyze time series data to detect trends and generate forecasts

●   Evaluate AI model performance and communicate findings with appropriate technical and ethical context

●   Apply evidence-based strategies for self-directed learning and time management

●   Identify personal learning patterns and develop targeted approaches to address gaps

●   Build habits of reflection and self-assessment to sustain progress across the program

●   Develop resilience and problem-solving approaches for navigating academic challenges

●   Write clearly and precisely for technical and non-technical audiences

●   Structure and deliver verbal presentations of technical work

●   Translate complex technical concepts into accessible language for general audiences

●   Collaborate effectively with teammates through written and verbal communication

●   Investigate a complex real-world problem through research and stakeholder analysis

●   Design and prototype a technology-based solution to address the identified challenge

●   Apply engineering principles within the constraints of real societal and environmental contexts

●   Collaborate effectively in a team environment with shared accountability for outcomes

●   Communicate findings and proposed solutions to external audiences

●   Advance a technical solution from prototype to a more developed, tested implementation

●   Apply leadership and team coordination skills in a self-directed project environment

●   Integrate feedback from real stakeholders to improve solution design and effectiveness

●   Document and present the evolution of your solution with technical and contextual rigor

●   Define a focused, researchable question in a chosen area of computer science

●   Conduct a structured review of existing literature and professional practice

●   Design a research methodology appropriate to the question and available resources

●   Produce a research proposal that meets academic and professional standards

●   Define and execute an original technical project from research through implementation

●   Apply skills from across the degree to solve a real, self-identified problem

●   Document and present your project to technical and non-technical audiences

●   Reflect on your growth as a technical practitioner and articulate your professional readiness

●   Craft an effective resume, portfolio, and LinkedIn presence for the technical job market

●   Prepare for and practice technical and behavioral interviews

●   Develop a personal professional brand that reflects your skills and goals

●   Navigate the job search process, including outreach, applications, and offer evaluation

●   Apply academic programming and software development skills in a professional context

●   Navigate real workplace dynamics, including communication, feedback, and team collaboration

●   Deliver work that meets the standards and timelines of a professional software team

●   Reflect on the gap between academic and professional practice and identify areas for growth

●   Take on increased technical responsibility within a professional software environment

●   Apply more advanced skills from the degree program to real employer challenges

●   Develop independence and professional judgment in navigating complex work situations

●   Build and articulate a documented record of professional contribution

●   Apply academic programming and software development skills in a professional context

●   Navigate real workplace dynamics, including communication, feedback, and team collaboration

●   Deliver work that meets the standards and timelines of a professional software team

●   Reflect on the gap between academic and professional practice and identify areas for growth