Data Analytics - Graduate

The Graduate Certification in Data Analytics is ideal for Amberton students who desire to enhance their quantitative toolkit, gain skills in a high-demand field, and analyze data to derive meaningful and actionable insights. The curriculum focuses on the fundamental concepts a data analyst would use which include basic statistical concepts necessary for analytics; proper design, development, and uses for databases; predictive analytical techniques such as linear and logistic regression, decision trees, and machine learning algorithms; and both traditional and modern ways to display and visualize data. Throughout the certification, students will be exposed to modern analytical software common to industry professionals. Classes are taught at an applied, practitioner level where upper-level math and complex programming skills are not required.

After the successful completion of the four courses, students will not only have mastered competencies required for data analytics within organizations, but will also have completed 12 hours of college credit toward a degree.  This certification may be completed online with five of the University’s graduate degrees.

Students completing a Data Analytics Certification will be able to:

• Understand basic concepts of probability and their application to data analytics.
• Perform basic descriptive and inferential statistics to include (but not limited to) measures of central tendency and dispersion, confidence intervals, and hypothesis tests.
• Describe the basic tenets central to designing and developing a quality database and be able to understand the role databases play in storing complex data.
• Differentiate between the various types of predictive analytical techniques that exist, and successfully apply each one to a data set and interpret the results.
• Apply the fundamental concepts of data visualization to create meaningful displays of data.
• Evaluate a research question, develop testable hypotheses, and be able to apply the correct statistical technique(s) to derive an actionable insight.