Graduate Certificate in Applied Data Science
Post-Baccalaureate Certificate
This certificate is designed to provide hands-on training in the area of applied data science. Coursework focuses on developing knowledge and skills in critical reasoning, measurement development, evaluation, data management, data analytic software utilization, multivariate data analysis and modeling, data visualization, machine learning, data mining, cloud computing, and big data techniques.
The Applied Data Science (ADS) Certificate program is offered online through the Engineering Graduate Programs office in the College of Engineering & Science.
Program Outcomes
Upon completion of the Applied Data Science Graduate Certificate, graduates will be able to:
- apply data science concepts and methods to solve problems in real-world contexts;
- demonstrate competencies in data mining and machine learning techniques, including classification, clustering, feature extraction, visualization, and dimensionality reduction;
- use statistical software packages to apply a variety of statistical techniques to diverse data types and structures;
- demonstrate an understanding of the strengths, limitations and assumptions of specific statistical methods;
- develop the ability to build and assess data-based and machine learning models as well as an understanding of model implementation in real-world settings.
CSSE 5110 is a co-requisite or prerequisite for all other requirements, so should be taken first.
Required Courses (9 credit hours)
| CSSE 5110 | Quantitative Foundations for Data Analysis (3 credits) |
| CSSE 5120 | Introduction to Data Science (3 credits) |
| CSSE5310 | Data Mining (3 credits) |
Elective courses (choose two courses - six credit hours)
| CSSE 5480 | Artificial Intelligence (3 credits) |
| CSSE 5560 | Database (3 credits) |
| CSSE 5580 | Cloud Computing and Big Data (3 credits) |
| CSSE 5910 | Data Science Applications (3 credits) |
| DATA5060 | Advanced Statistics for Applied Data Analytics (3 credits) |
| ELEE 5350 | Machine Learning (3 credits) |
| ELEE 5750 | Deep Learning (3 credits) |
Admissions Criteria
This is a 15-credit (five-course) certificate program. Nine credits (three courses) are required core courses, and six credits (two courses) are electives, which may be chosen from the list below.
Students must maintain a minimum 3.0 GPA in both the certificate program and overall. Grades below "C" will not advance a student towards graduation.
Program Requirements
Applicants for the Applied Data Science Graduate Certificate must hold a bachelor's degree (or equivalent) in computer science, engineering, or a closely related field with a minimum GPA of 3.0. They must have basic experience in programming using a modern programming language such as R or Python. Each applicant must also be approved by the department chair/director and the College of Engineering & Science dean's office.