Certificate in Data Analytics
Overview
The Certificate in Data Analytics offers students the opportunity to explore concepts of data and statistical analysis through project-based curriculum. Certificate students will be prepared for advanced data analysis academic programs at the undergraduate and graduate level.
Student Learning Outcomes
Upon successful completion of this certificate, students will be equipped to:
- Use data analysis tools such as SAS or Python.
- Develop and test hypotheses about data.
- Apply the appropriate statistical test to specific data and questions.
- Use basic statistical principles to answer questions developed.
- Apply, test, and interpret machine learning algorithms to address research questions.
- Produce professional reports representing data analysis.
- Effectively communicate data and statistical findings.
Admission Requirements
All courses in the Data Analytics Certificate must be completed and approved through the Accelerated Online Degree Program.
Transfer Credit
Transfer credit may be considered on a case-by-case basis after an application has been submitted.
Certificate Requirements
Certificate in Data Analytics (12 credit hours)
Complete the following:
Not all courses are offered every year. The certificate is successfully finished when all certificate courses are completed with grades of C- or better and a certificate GPA of 2.0 or above.
In this course, students will learn how to apply basic data analysis tools using their choice of SAS or Python or both. Students will begin to develop research skills by developing a research question and conducting a literature review. Students will develop skills in generating testable hypotheses, understanding large data sets, managing data, conducting statistical analyses, and presenting results to expert and novice audiences. Through this course, students will learn foundational concepts of data management and visualization.
In this course, students will develop and test hypotheses about data through the use of various statistical tests, utilizing data analysis tools of SAS or Python. Students will continue the refinement of their research questions to explore data analysis using statistical tests and tools.
This course focuses on machine learning processes of developing, testing, and applying predictive algorithms to achieve a goal. Students will learn about basic classification, decision trees, and clustering. Students will continue the refinement of their research questions to explore data analysis using statistical tests and tools including machine learning.
In this course, students will apply and refine the data analytic techniques learned from previous certificate courses to address a research question of choice. Using real world data, students will complete a project and present their findings to the class. Prerequisite: DATA 210: Introduction to Data Analysis and DATA 224: Data Analysis Tools