Data Analytics Certificate

This course introduces elementary concepts of probability and statistics including data types, graphs of qualitative and quantitative data, numerical summaries of data, concepts from probability, calculating probabilities of simple and compound events, and discrete random variables including binomial random variables. This course serves as a prerequisite for Statistics Fundamentals.

Statistics Fundamentals builds on the material covered in Introduction to Statistics. Topics covered include continuous distributions, including the normal distribution, sampling distributions, confidence intervals, hypothesis tests, two-sample problems, and regression models. An emphasis will be placed on discovering methods through simulation, and then correlating results with the established methods, such as formulas and tables, as well as an interpretation of results.

This course introduces the student to the fundamental concepts and techniques of relational database technology, structured query language, database design, and database management. Students perform hands-on labs with commercial software and databases based on real-world scenarios.

This introductory-level Python programming course teaches students how to analyze a problem and devise a program that solves the problem. Students learn Python syntax and fundamental concepts such as functions, exception handling, and Python data types. Students write their own programs, learn conditional logic, loops, and sequences, and apply what they've learned in hands-on lab activities.

This course will expose students to a typical analytics process from preparing project requirements to presenting project findings in verbal, written, and visual form. To achieve this, students will use a combination of tools, including Python and Tableau, to collect data, clean data, explore and analyze data, build data models, and prepare data visualizations.

The Data Analytics Capstone is the culminating course where students will apply the knowledge and skills gained through the data analytics certificate program to real-world problems in the work environment. The course is based on a data analytics challenge which students evaluate and prepare a presentation with their analysis. The goal of the capstone is to give students the opportunity to make meaningful connections between their learning and the workplace.