Machine Learning Certificate
The recent advances in machine learning (ML) have made significant impacts in diverse fields such as health care, agriculture, transportation, education, and global security, among others. Machine learning experts are in very high demand now and in the foreseeable future. The ML graduate certificate will prepare students to become data scientists, machine learning algorithm designers, deep learning systems engineers, computer vision experts, natural language processing specialists, software and application developers, and other machine learning–related professionals.
Program Related Information
Program Contact
Michelle Perone, Graduate Advisor
402.554.3819
mperone@unomaha.edu
Program Website
Admissions
General Application Requirements and Admission Criteria
Application Deadlines
- Spring 2027: November 1
- Summer 2027: March 1
- Fall 2027: July 1
Other Requirements
- Individuals with an undergraduate degree and one to two years of work experience in information systems (IS) related roles are eligible to apply for this certificate programs.
- The minimum undergraduate grade point average requirement for the data management certificate is 3.0 or equivalent score on a 4.0 scale. Applicants should have the equivalent of a 4-year undergraduate degree.
- English Language Proficiency: Applicants are required to have a command of oral and written English. Those who do not hold a baccalaureate or other advanced degree from the United States, OR a baccalaureate or other advanced degree from a predetermined country on the waiver list, must meet the minimum language proficiency score requirement in order to be considered for admission. Minimum scores required for this program are:
- Internet-based TOEFL: 80, IELTS: 6.5, PTE: 53, Duolingo: 110
- Resume: Submit a detailed resume indicating your work experience and background
Degree Requirements
| Code | Title | Credits |
|---|---|---|
| Recommended Prerequisite Course | ||
| INTRODUCTION TO DATA ANALYTICS USING PYTHON | ||
| Required Courses | ||
| CSCI 8590 | FUNDAMENTALS OF DEEP LEARNING | 3 |
| CSCI 8476 | PATTERN RECOGNITION | 3 |
| If a required course has already been completed through a similar or equivalent course, it must be replaced with another course from the electives list below. | ||
| Electives | 6 | |
| ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE | ||
| IMAGE PROCESSING AND COMPUTER VISION | ||
| DATA WAREHOUSING AND DATA MINING | ||
| MACHINE LEARNING FOR TEXT | ||
| ADVANCED TOPICS IN NATURAL LANGUAGE UNDERSTANDING | ||
| NUMERICAL LINEAR ALGEBRA | ||
| Total Credits | 12 | |
