Data Analytics (Certificate)

18 Credits | Main Campus

Demand for digital competence is on the rise and the certificate in Data Analytics offers the digital fluency demanded by an increasingly data-driven and decision-making digital tech workforce.

Trinity Washington University offers a certificate in Data Analytics for students who want to pursue careers in digital technology. The demand for digital competence is on the rise and the certificate in Data Analytics 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 Data Analytics 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 certificate credential, students will master key concepts of data analysis and increase their marketability in the digital technology industry.

A minor in Data Analytics is also available to students enrolled in the College of Arts and Sciences.

Earn a Generalist Credential

Students with a certificate in Data Analytics 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 program requirements, students will receive a digital badge to display on their LinkedIn profile or resume.

Trinity Washington University joins other universities in the region to offer such a credential. District universities in the CoLAB network include George Mason, American, George Washington, and Howard. Participating businesses include Amazon, Medstar Health, General Dynamics, Northrop Grumman, JP Morgan Chase & Co, Deloitte, CapitalOne, and McKinsey.

What You’ll Learn

Differentiate between different types of data analysis techniques and appropriately apply each type in real life scenarios
Demonstrate knowledge of descriptive statistics, probability, and hypothesis testing
Visualize data using various types of commonly used displays: tables, dashboards, graphs, maps, etc.
Evaluate a problem in context to determine the appropriate data to use, how to analyze it, and deliver a compelling visualization to answer a question.
Identify the ethical and legal constraints of data collection, aggregation, and analysis.
Explain the benefits and challenges and how to work with Big Data
Perform basic data manipulation and apply concepts learned in your classes to solve problems using Excel, SQL, and R