Program Overview
Discover the Advantages of Our Online M.S. in Applied Digital Technology – Artificial Intelligence and Machine Learning
Position yourself in the forefront of today's technology-driven world with an online Master of Science in Applied Digital Technology with a Concentration in Artificial Intelligence and Machine Learning from Arkansas State University. Become an expert in AI and machine learning as careers in AI are projected to soar according to the U.S. Bureau of Labor Statistics.



This program will empower you with core business competencies as you discover how information systems aid managers in decision making, learn the principles of project management, and study current topics pertinent to management and society. Discover machine learning trends along with architecture and programming concepts. Develop AI and machine learning solutions and deployment options to drive efficiency and success for your organization.
Designed for flexibility, this online program can be customized with a blend of business and technology electives to meet your personal and professional goals.
A-State is High Quality
A-State is recognized among the U.S. News & World Report's "Top Public Schools, National Universities" for 2023.
In this 100% online M.S. in Applied Digital Technology – AI and Machine Learning, you will learn how to:
- Effectively communicate the business requirements for technology-related projects
- Understand the impacts of technology decisions on management and business operations
- Apply project management concepts to manage a project from concept to delivery
- Tailor a portion of your degree with a second area of emphasis or a blend of business- and technology-related elective courses
- Understand and utilize design, development, and deployment concepts in AI and machine learning in business situations
As a graduate of the M.S. in Applied Digital Technology – AI and Machine Learning program, you will be prepared for advancement into roles such as:
- Project Manager
- Director of Process Improvement
- Implementation Analyst
- Automation Implementation Manager
- Product Manager
- Digital Application Manager
Also available online at A-State:
Tuition
Learn About Tuition to Fit Your Budget
Our online M.S. in Applied Digital Technology – AI and Machine Learning program offers the same affordable tuition to all U.S. residents. All fees are included.


Per Credit Hour | Per Course | ||||
---|---|---|---|---|---|
U.S. Resident Tuition | Required Fees | Total | U.S. Resident Tuition | Required Fees | Total |
$300.00 | $40.00 | $340.00 | $900.00 | $120.00 | $1020.00 |
A-State is Top Ranked
A-State is ranked among the "Top 10 Best Colleges in Arkansas" by CollegeChoice.net, 2021
Calendar
Follow these Dates to Apply, Enroll and Start Classes
Ideal for working professionals, Arkansas State online programs are delivered in an accelerated format with multiple start dates each year.
Next Start & Application Due Dates:


Term | Length | Course Begin | Course End | Application Deadline | Document Deadline | Registration Deadline | Payment Deadline | Last Day to Withdraw |
---|---|---|---|---|---|---|---|---|
Summer 2023 | 5 wk | 05/30/2023 | 06/30/2023 | 05/15/2023 | 05/19/2023 | 05/25/2023 | 05/26/2023 | 06/19/2023 |
5 wk | 07/03/2023 | 08/04/2023 | 06/19/2023 | 06/23/2023 | 06/29/2023 | 06/30/2023 | 07/21/2023 | |
Fall 2023 | 7 wk | 08/21/2023 | 10/06/2023 | 08/07/2023 | 08/11/2023 | 08/17/2023 | 08/18/2023 | 09/22/2023 |
7 wk | 10/16/2023 | 12/08/2023 | 10/02/2023 | 10/06/2023 | 10/12/2023 | 10/13/2023 | 11/17/2023 | |
Spring 2024 | 7 wk | 01/08/2024 | 02/23/2024 | 12/15/2023 | 12/19/2023 | 01/04/2024 | 01/05/2024 | 02/09/2024 |
7 wk | 03/04/2024 | 04/26/2024 | 02/19/2024 | 02/23/2024 | 02/29/2024 | 03/01/2024 | 04/05/2024 | |
Summer 2024 | 5 wk | 05/28/2024 | 06/27/2024 | 05/14/2024 | 05/17/2024 | 05/23/2024 | 05/24/2024 | 06/14/2024 |
5 wk | 07/02/2024 | 08/01/2024 | 06/18/2024 | 06/21/2024 | 06/27/2024 | 06/28/2024 | 07/26/2024 |
Admissions
Get Started by Checking these Admission Requirements
A-State Online offers a streamlined admission process to help you get started quickly and easily. To be admitted to the M.S. in Applied Digital Technology – AI and Machine Learning online program, you must have a bachelor's degree from an accredited institution.
-
Bachelor's degree from an accredited university with at least a 2.5 cumulative GPA or a 2.75 in the last 60 hours (undergraduate, graduate or combination thereof)
or
Graduate or post-baccalaureate professional degree from a regionally accredited (U.S.) institution
- If you have lower than a 2.5 cumulative GPA and less than a 2.75 in the last 60 hours, you may still apply for consideration for admittance by including a statement of purpose as part of the application. Please contact an Enrollment Services representative at 866-621-8096 866-621-8096 for more information
Note: If you are admitted and have less than a 2.75 cumulative GPA and less than a 3.0 GPA in the last 60 hours, you must make a grade of B or better in each course during the first 9 hours of graduate work at Arkansas State University. Additionally, you will only be allowed to enroll in one course (or 3 graduate hours) per 7-week session for the first two sessions.
- Complete online application
- Submit a nonrefundable $30 fee.
- Have official transcript(s) sent from the registrar of the college/university attended. Official transcripts are sealed transcripts sent from the granting institution.
Additional Information
Submit all documents to:
A-State OnlineP.O. Box 2520
State University, AR 72467
Fax: 870-972-3548
Email: [email protected]
For Non-US Postal Mail Overnight Delivery Only:
Academic Partnershipsc/o Central Receiving
2713 Pawnee St.
Jonesboro, AR 72401
Courses
Browse the Courses in Your Online M.S. in Applied Digital Technology – AI and Machine Learning
To graduate from the M.S. in Applied Digital Technology – AI and Machine Learning online program, you must complete a total of 33 credit hours. Required coursework includes four core courses (for a total of 12 credit hours), four concentration courses (for a total of 12 credit hours) and three elective courses (for a total of nine credit hours).
MBA 5003: Graduate Business Fundamentals
Duration: 7 weeks | Credit Hours: 3
The course focuses on the essentials of core business functions with an emphasis on integrating applied business statistics, economics, financial accounting, and corporate finance. This course ensures that students have the required business acumen to succeed in the graduate business core.
MIS 6413: Management Information Systems
Duration: 7 weeks | Credit Hours: 3
The spectrum of the information needs of organizations. (1) Provides understanding of the uses of information by operational subsystems such as production, finance, marketing, personnel, etc. (2) Provides an analysis of the information needs of middle and top-level management, and the use of information systems to aid managers in the decision-making process. (3) Provide student with an understanding of the use of information systems to gain competitive advantage and how to manage information as an organizational resource.
MIS 6493: Seminar in Information Systems
Duration: 7 weeks | Credit Hours: 3
A study of new concepts, topics, and is- sues in Information Systems as heralded in current literature. Students are expected to research and report on pertinent topics as to the effects on management and the impact on society.
MGMT 6023: Fundamentals of Project Management
Duration: 7 weeks | Credit Hours: 3
Examines the practice and principles of project management. Topics include identifying and selecting projects, developing project proposals, sequencing workflows, estimating project duration, and budgeting.
DIGI 5023: Introduction to Machine Learning
Duration: 7 weeks | Credit Hours: 3
Future trends in machine learning and their impact on society through case studies/use cases.
DIGI 5063: Analysis and Design of AI
Duration: 7 weeks | Credit Hours: 3
Analyzation of AI use cases and completion of both high-level and low-level design.
DIGI 6023: Design and Development of AI
Duration: 7 weeks | Credit Hours: 3
Architecting and machine learning as well as Python programming concepts related to AI and machine learning.
DIGI 6033: AI Deployment Solutions
Duration: 7 weeks | Credit Hours: 3
Development of AI and machine learning solutions and the practice of various deployment options such as public cloud deployments.
Students must select three courses (nine credit hours) from other tracks within the M.S. in Applied Digital Technology program or advisor-approved courses in business and statistics.