Trinity offers a minor in Data Analytics for students majoring in any subject in the College of Arts and Sciences who want to pursue careers in digital technology. The demand for digital competence is on the rise and the Data Analytics minor offers the digital fluency demanded by an increasingly data-driven and decision-making digital tech workforce.
Data Analytics is the process of effectively examining and interpreting datasets to draw a conclusion. The minor curriculum will sharpen critical thinking and problem-solving skills, strengthen scientific literacy, and build proficiency in statistical programming. The program also promotes social awareness and communication. With a minor in Data Analytics, students will master key concepts of data analysis and increase their marketability in the digital technology industry.
A Data Analytics certificate is also offered through the School of Professional Studies.
Required Courses (18 credits)
ITEC 100 Introduction to Data AnalyticsUnderstanding data is the key to understanding the world. Whether as a consumer or working for top companies, being able to collect, analyze, and present data provides us with invaluable insights and skills. Data analytics is the process by which useful information is extracted from large amounts of data. This course is designed to explain the importance of data, differentiate between common data typologies, and introduce the data analytics process. The course provides students with the necessary knowledge to better understand how data can be used to reduce uncertainty related to decision making. Additionally, it introduces students to a set of widely used data mining tools, techniques, and applications using R software. Case studies and practical examples will be extensively presented throughout the course.
Pre: MATH 110
CMSC 111 Introduction to ProgrammingServes as an entry-level programming course recommended for all students. Objects, arrays, program flow (if-then-else, while, do-while, for, switch), simple graphical user interfaces and applets, problem solving techniques, and elementary algorithms are covered. Effective design, implementation, debugging, and documentation of object-oriented programs are emphasized. Formerly MAT 141 Introduction to Programming.
MATH 215 Prob & Stats with ApplicationsPresents basic principles of probability and statistics, with applications to diverse fields of study. Topics include review of data and data measurement, probability, hypotheses testing and inference, regression modeling, and more. Imparts practical skills through real world case studies, applied exercises, and analyses using spreadsheet software such as Excel. For non-math majors or minors in the data analytics and bioinformatics pathways.
Prerequisites: MATH 102 or MATH 108 or MATH 109
ITEC 210 Data Visualization and CommunicationData visualization allows us to tell a story and effectively communicate results from large datasets. Data visualization and communication techniques are important for any job dealing with data, including but not limited to business analytics, data analytics, statistics, and STEM jobs. In this course, students will learn about the role of data visualization in a variety of academic fields and distinguish between the types of visualization techniques available. We will use Excel and R primarily to create static and interactive data visualizations including tables, graphs, maps, and trees. Students will also gain a deeper understanding of data analysis as they critically approach a problem to evaluate the best fit visualization to reach various audiences using real life scenarios and data structures. Data Analytics is a prerequisite for this course.
ITEC 304 Data ManipulationA key component of data analytics is understanding how to create, clean, and manipulate large amounts of information stored in databases. By mastering data management skills and techniques, data scientists in a variety of fields can design and evaluate large datasets. In this course, students will become familiar with data manipulation and cleaning techniques as well as understand the importance and challenges of working with large data. Case studies using data and real-life scenarios from Business, STEM, and Criminal Justice fields will add context and hands on experiences for students. By the end of the course, students will be able to use Excel, SQL, and R to create, edit, and manage large amounts of information and data. Data Analytics is a prerequisite for this course.
Prerequisites (CAS ONLY): ITEC 100
PHIL 281 The Ethics of Data AnalyticsThis course explores the ethical issues related to the collection, aggregation, analysis, and commercial/political implementation of internet data. Students will investigate the possible threats to personal privacy and to the exercise of autonomy posed by the corporate/governmental collection, aggregation, and analysis of data. The course probes the ethical questions posed by the utilization of internet data research to shape future consumer and political behaviors. Students will also study the potential social biases reinforced or created by data analytics models. These issues will be framed and analyzed within the context of utilitarian and deontological ethical theory. The course will also examine the responsibility of corporate and governmental institutions to safeguard data and restrict its use to legitimate purposes. Finally, the course surveys the relationship between the legal and ethical limitations on the utilization of internet data research.
Prerequisites: PHIL/COM 150
Students who minor in Data Analytics, in conjunction with their major, could benefit from the partnership with Capital CoLAB’s Digital Tech Credential program (Collaborative of Leaders in Academia and Business). Students could earn The Generalist Credential that prepares any major for job roles that require an understanding of data analysis. A Generalist credential opens opportunities for job shadowing, engagement with senior executives, mentoring/coaching, resume review, and priority interviews for internships. Upon completion of the minor requirements, students will receive a digital badge to display on their LinkedIn profile or resume.
Credits earned through AP examinations do not fulfill requirements of the minor.
Credits earned through CLEP examinations do not fulfill requirements of the minor.
Grades in Required Courses:
Students are required to earn a grade of “C” (2.0) or better in all courses counted to fulfill requirements for the minor.
With the exception of internships, courses fulfilling minor requirements may not be taken pass/no pass.
Students may meet minor requirements with courses taken during study abroad.
The Data Analytics minor supports and encourages Trinity’s TELL Program. Students applying for experiential learning credit should consult with the program faculty.
Transfer credit from appropriately accredited institutions of higher learning may be counted for minor requirements, dependent on program review and approval. Associations recognized by the United States Department of Education (USDE) and the Commission on Higher Education (CHEA) confer appropriate accreditation; these associations include but are not limited to regional accreditors.