Graduate Certificate in Data Science
About the Program
This certificate program aims to provide interdisciplinary training in the important aspects of the rapidly emerging area of data science. With large volumes of data being generated every day from multiple sources, the importance of systematic and rigorous approaches to understanding and putting this data to good use is now well recognized.
The specific objectives of the certificate program are to provide training on data collection, storage, manipulation, visualization, and privacy; provide a strong background in programming, algorithms, and methods for statistical analysis in data mining and machine learning; train students in the use of software tools and systems for processing big data; and educate students on ethical issues, management, policies, and legal requirements in data science.
This program has been approved by the federal government to be financial aid eligible.
A flyer for the program is available.
Students must complete 12 hours (4 courses) from the following coursework with at least a 3.0 average:
At least 6 hours of data science core courses
6 hours of electives:
- Data Mining
- Information Retrieval
- Neural Networks
- Machine Learning
- Natural Language Processing
- Mathematical Models
The certificate program may be pursued concurrently with other graduate programs at the University. In particular, students currently admitted to a graduate program at the UofM may join this certificate program. To apply, students must submit:
- Application form
- Transcripts of prior graduate study
- Two letters of recommendation
For detailed admission and program requirements, please refer to the University's Graduate Catalog.
This certificate program is available fully online. The course requirements for the online option are the same as those for the traditional program, but note that only some course options are available online. Please apply using the same link for traditional students below. Questions about the online program can be directed to email@example.com.