Computer Information Technology (CIT)

CIT 112. Introduction to Computer Science. 3 Credit Hours.

Introduction to Computer Science provides a survey of technical topics related to computer systems, emphasizing the relationships between hardware, cloud architecture, systems, and application software. It explores algorithms, data storage and manipulation, networking and the Internet, number systems, data representation, data structures, database systems, processor architecture, operating systems functions, and concepts of programming languages.
Prerequisites: Reading Proficiency
Recommended Preparation: Basic computer literacy is expected

CIT 125. Introduction to Databases. 3 Credit Hours.

Introduction to Databases introduces students to the fundamental concepts, theories, and practices underlying the design, implementation, and management of databases. Throughout the course students explore various types of databases, including relational, NoSQL, and object-oriented databases, and gain a thorough understanding of their structures, functionalities, and applications. The course covers a wide range of topics, including database modeling, schema design, normalization, query languages, transaction management, data integrity, and security concepts. Students learn how to design and create a basic relational database schema using entity-relationship diagrams (ERDs) and implement them using Structured Query Language (SQL). This course is aligned to the Google Data Analytics course.
Prerequisites: Reading Proficiency

CIT 141. Introduction to UX/UI Design. 3 Credit Hours.

Introduction to UX/UI Design introduces the fundamentals of User Experience (UX) and User Interface (UI) design, pivotal components in creating effective and engaging digital products. Designed for beginners and intermediate designers alike, this course explores the principles of design thinking, user-centered design, and the interplay between visual aesthetics and functional usability. Through a blend of theoretical knowledge and practical exercises, students will learn how to craft intuitive interfaces and seamless user experiences. Emphasizing hands-on learning, the course covers the latest tools and techniques used by professionals in the field, like Adobe XD, Sketch, and Figma. Upon completion of this course, students will be able to tackle real-world projects. This course aligns with the Google UX Design Certificate.
Prerequisites: Reading Proficiency

CIT 151. Computer Applications in Business. 4 Credit Hours.

Computer Applications in Business covers software programs frequently used in the business environment. It introduces word processing, spreadsheets, database management, web-based email, presentation software, cloud-based tools and collaboration software.
Prerequisites: Concurrent or prior enrollment in IS 122 or IS 123 or IT 102 or HIM 102 or CIT 112 with a minimum grade of "C" or equivalent experience and Reading Proficiency

CIT 155. Cloud Database Management. 4 Credit Hours.

Cloud Database Management focuses on equipping students with the knowledge and skills necessary to effectively manage databases in the cloud using Amazon Web Services (AWS) and Azure platforms. Students explore the intricacies of configuring, optimizing, and securing cloud-based database solutions.
Prerequisites: CIT 125 and CIT 151 with minimum grades of "C", and Reading Proficiency

CIT 160. Introduction to Data Visualization. 3 Credit Hours.

Introduction to Data Visualization empower students with the skills and knowledge needed to transform complex datasets into clear, informative visual representations. Students explore the principles, tools, and techniques essential for creating compelling data visualizations that drive understanding and decision-making. Hands-on activities provide opportunities for participants to compare different visualization tools, applying their understanding to select the most suitable software for specific visualization tasks. Students synthesize their learning by combining multiple data sources into cohesive visualizations, demonstrating proficiency in advanced techniques such as interactive dashboards and animations.
Prerequisites: Concurrent or prior enrollment in CIT 125 and CIT 151 with minimum grade of "C" and Reading Proficiency

CIT 166. Programming I with C# and Java. 4 Credit Hours.

Programming I with C# and Java teaches students software development problem-solving methodologies utilizing current software design and development tools and techniques. Students are also introduced to the C# and Java programming languages. Topics include data structures, program design, pseudocode, language control structures, procedures and functions, error handling, and object-oriented design using classes. Basic computer literacy is required.
Prerequisites: Reading Proficiency

CIT 180. Programming I with Python. 3 Credit Hours.

Programming I with Python introduces students to the foundational concepts of computer programming using Python. Students learn to think computationally and solve complex problems through lectures, hands-on exercises, and collaborative projects. The course emphasizes problem-solving analysis, program specifications, algorithm design, and exploring data structures and algorithms. By also exploring Object-Oriented Programming (OOP), students acquire a robust toolkit for tackling real-world programming challenges. Additionally, the course focuses on the importance of clear code documentation with flowcharts, pseudocode, and code recognition techniques. This course is aligned with the Python Institute PCEP - Certified Entry-Level Python Programmer Certification.
Prerequisites: Reading Proficiency

CIT 257. Advanced Data Analytics. 3 Credit Hours.

Advanced Data Analytics is designed for students who have completed foundational courses in database systems, data analytics, and cloud database management. This course explores more advanced data analytics techniques, exploring complex data models, machine learning algorithms, big data technologies, and their applications in cloud environments. Students engage with real-world datasets, utilizing advance tools and platforms like Python, R, Spark, MongoDB, and Hadoop in cloud settings such as Azure and Amazon Web Services (AWS) to perform predictive modeling, data mining, and comprehensive data analysis. Emphasis is on interactive learning, including hands-on projects, case studies, and collaborative research tasks, to prepare students s in the field of data science and analytics.
Prerequisites: CIT 125, CIT 285, and CIT 155 with minimum grades of "C", and Reading Proficiency

CIT 266. Programming II with C# and Java. 4 Credit Hours.

Programming II with C# and Java builds upon the foundations of Programming I with C# and Java. This course takes an in-depth approach to programming with object-oriented programming, covering advanced topics such as inheritance, polymorphism, encapsulation, interfaces, abstract classes, exception handling, and collections. Students develop more complex applications, emphasizing connecting to data sources, code efficiency, and design patterns.
Prerequisites: CIT 166 with minimum grade of "C" and Reading Proficiency

CIT 285. Principles of Data Analytics. 3 Credit Hours.

Principles of Data Analytics explores the fundamental principles of data analysis techniques and statistical modeling. Students utilize higher order thinking skills, including applying statistical models, analyzing data to uncover patterns and trends, and critically evaluating the reliability of analytical findings. Students also engage in problem-solving activities, designing and implementing data analysis pipelines using programming languages and software tools.
Prerequisites: CIT 125 with a minimum grade of "C" and Reading Proficiency

CIT 291. Workplace Learning: Computer and Information Technology. 3-4 Credit Hours.

Workplace Learning: Computer and Information Technology consists of a workplace assignment with an employer or agency, or an internship project. Students will complete a minimum of 100 hours and a maximum of 150 hours of internship during the semester, which allows the student to apply skills learned in the classroom. Students will have the opportunity to learn new skills and explore career possibilities while supervised by the employer and a faculty member. Students will also learn career readiness skills, resume writing, cover letter writing, interview techniques, video interview, and soft skills development. This course is appropriate for students nearing completion of their technology degree and preparing for internship or employment.
Prerequisites: Enrollment in a CIT or IT program, department approval, and Reading Proficiency
Recommended Preparation: Portfolio is recommended