Data Science, Graduate Certificate
School of Informatics, Computing and Cyber Systems
College of Engineering, Informatics, and Applied Sciences
Graduate certificate programs require a minimum of 12 credit hours. Many certificate programs require more than 12 credit hours.
No more than one 400-level NAU course (3 or 4 units) may be used on a certificate program.
No more than 25% of the units required for the certificate program may be transferred from another university.
A 400-level course (undergraduate course) completed at another university is not eligible for transfer credit.
A minimum grade point average of 3.0 must be achieved to obtain a graduate certificate. No more than three units of coursework with a grade of "C" may be used in a certificate program.
A graduate student may pursue a graduate certificate concurrently with a graduate degree. Each graduate degree program must decide which, if any, certificate courses can be counted toward the graduate degree.
Students who are admitted to a graduate certificate program will be eligible for the official posting of the graduate certificate to their transcripts when all applicable coursework has been successfully completed and approved by the academic unit and the Graduate College.
- Please be aware that federal financial aid is not available for some certificates, if the certificate is pursued and completed as a stand-alone certificate (i.e., not completed concurrently with a degree program). See the “Details” tab for additional information.
In addition to University Requirements:
- Complete individual plan requirements.
|Minimum Units for Completion||18|
|Additional Admission Requirements||Required|
The graduate certificate in Data Science will augment students’ individual graduate programs of study with additional skills enabling them to efficiently and correctly collect, process, store, and analyze large-scale data sets. Interdisciplinary coursework provides students with expertise in programming in a contemporary high-level programming language, data structures and programming techniques particularly appropriate for large data sets, the application of machine learning and data mining algorithms, and the use of a wide range of statistical methods, including analysis of variance and covariance and multivariate analysis. With the completion of this certificate, students interested in academic careers will be able to design and efficiently implement appropriate quantitative data analyses in their own specific area of research. Given the emerging centrality of data-driven analyses in science, engineering, business, art, and the humanities, students will be better prepared to be successful in professional practice. This certificate is designed for any student with an interest to apply data analysis techniques in their own area of interest.
Student Learning Outcomes
Graduates will this certificate will demonstrate the following competencies and program learning outcomes:
- Identify, explain, synthesize, and apply fundamental skills in computer science, including programming in a high-level programming language, data structures particularly appropriate for large data sets, and machine learning and data mining algorithms
- Identify, explain, synthesize, and apply a wide range of statistical methods, including analysis of variance and covariance and multivariate analysis
Additional Admission Requirements
- Admission requirements over and above admission to NAU are required.
- NAU Graduate Online application is required for all programs. Details on admission requirements are included in the online application.
- Undergraduate degree from a regionally accredited institution
- Grade Point Average (GPA) of 3.00 (scale is 4.00 = "A"), or the equivalent.
- Admission to many graduate programs is on a competitive basis, and programs may have higher standards than those established by the Graduate College.
- For details on graduate admission policies, please visit the Graduate Admissions Policy
- International applicants have additional admission requirements. Please see the International Graduate Admissions Policy
Individual program admission requirements include:
- Prior experience in programming and statistics, as evidenced by either a) at least one undergraduate course in each of these fields or b) relevant applied experience.
- Personal statement outlining the prospective student’s professional goals in data science and either a) a list of undergraduate courses in programming and statistics or b) a description of relevant applied experience.
Take the following 18 units:
This certificate may be pursued and completed concurrently with a degree program or as a stand-alone certificate. Federal financial aid cannot be used if the certificate is completed as a stand-alone certificate.
Be aware that some courses may have prerequisites that you must also take. For prerequisite information click on the course or see your advisor.