Online Artificial Intelligence Graduate Certificate
Accelerate Your Career in a Growing Field
Learn to use innovative AI skills to solve business problems with the online Artificial Intelligence graduate certificate from Saint Mary’s University of Minnesota. The program takes a hands-on approach to exploring data engineering and the Internet of Things (IoT), designing data collection methods, and programming deep learning models.
This certificate is a part of Saint Mary’s Accelerators, a carefully crafted series of master’s-level graduate certificates designed to advance your career. After completing the program, you may apply your credits to the Master of Science in Business Intelligence and Data Analytics (BIDA) degree and finish your education faster.**
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Why Earn Your Artificial Intelligence Certificate Online with Saint Mary's?
Artificial intelligence technologies are taking the business world by storm. With the online Artificial Intelligence graduate certificate, you can become a qualified expert in this growing, in-demand field in less than one year. Learn from experienced faculty in a convenient online platform and take the lead in your business career with artificial intelligence expertise.
Program Highlights
- Digital Badging for all Graduate Certificate Courses
- Apply Graduate Certificate Credits to an MS BIDA and MBA
- No Prerequisite Courses or GRE/GMAT Required
Course List & Requirements
Saint Mary’s online Artificial Intelligence certification program provides a foundational introduction to big data, IoT, and artificial intelligence. You will study data engineering to collect, clean, and structure data for AI projects. Courses are taught by expert faculty who bring valuable field expertise into the classroom. This program includes 12 credits of project-based coursework, preparing you to apply innovative AI-based solutions to business strategy, improving outcomes for organizations of all types.
BIA 630 Data Analysis and Business Modeling (3 credits)
This course introduces advanced concepts in predictive modeling and techniques to discover patterns in data, identify variables with the most predictive power, and develop predictive models. Students are introduced to descriptive, predictive, prescriptive analytics, and optimization models. The course utilizes Microsoft Excel to engineer and analyze business models. Students identify the proper use of complete regression, optimization, and exponential smoothing models.
Upon completion of this course, students are expected to be able to do the following:
- Utilize datasets to develop statistics and probability to predict future outcomes
- Implement appropriate models needed to analyze and critically evaluate business objectives
- Develop written and oral communication skills required to report on data-intensive business situations
- Organize data-intensive content in a professional setting
- Execute advanced analytics techniques
DIGA 620 Data Engineering (3 credits)
The course utilizes the data processing requirements necessary to implement technology-based analytics. The course explores the strengths and limitations of various data formats to make better decisions. The importance of structured and unstructured data formats and performing methods of data extraction, transformation, and loading are covered. Data wrangling methodologies explore constructing custom data pipelines to support efficient analysis. These methods include cleaning, filtering, standardizing, and categorizing data. Processes to review data for accuracy, consistency, and completeness are covered as well as techniques to mitigate error and improve data integrity. The course also investigates the legal and ethical considerations of data management.
Upon completion of this course, students are expected to be able to do the following:
- Perform extract, transform, and load (ETL) processes using structured and unstructured data formats
- Assess data for error and implement techniques to improve data integrity
- Determine appropriate data formats for given situations
- Design and document processes for converting raw data into a product suitable for analysis
- Identify legal and ethical issues related to the processing and dissemination of data
BIA 680 Intelligence Fundamentals (3 credits)
This course focuses on the framework for utilizing the Python programming language for artificial intelligence applications. The course explores performing, creating, and scripting. Students gain experience in programming Python scripts and data science applications.
Upon completion of this course, students are expected to be able to do the following:
- Write high-quality, maintainable Python programs for deep learning
- Import Python libraries for artificial intelligence development
- Articulate and demonstrate the value and concepts of Python programming language for analytical modeling
- Apply mathematical operations and code aligned with standard machine learning techniques
- Finally, evaluate common approaches to artificial intelligence application development
BIA 645 Communications and Content Strategies (3 credits)
Note: Students may choose either BIA 645 or BIA 681.
This course focuses on explaining complex datasets, models, and analysis to a variety of stakeholders including internal and external organizations and personnel of various disciplines. Audience analysis, and effective strategic communication are studied. Students identify and analyze problems. Professionalism in both oral and written communication is expected.
Upon completion of this course, students are expected to be able to do the following:
- Conduct stakeholder analysis and communications results
- Identify business problems and create analytical approaches to solve them
- Write reports based on best-practice data analysis frameworks
- Demonstrate best practice communication techniques to visualize, explore, and act on data science findings
BIA 681 Deep Learning Methodology (3 credits)
Note: Students may choose either BIA 645 or BIA 681.
This course introduces students to the complex nature of deep learning. First, by studying supervised and unsupervised models, students explore the benefits deep learning offers businesses. Then, using Python, students build a neural network model using the Keras framework and interpret the results for stakeholders.
Upon completion of this course, students are expected to be able to do the following:
- Communicate a conceptual understanding of why neural networks are gaining popularity
- Compare neural networks with other data structures and the situations in which neural networks should be used over other structures
- Visualize and interpret the components of a shallow neural network
- Construct a basic deep neural network model using Python and the Keras library
- Explain profound neural network model results for stakeholders
Course Catalog
Share Your Success
Saint Mary’s supports your success by providing you with the tools necessary to not only achieve your professional goals but to share them with the world—especially the digital world.
As part of our commitment, Saint Mary’s offers an opportunity for you to be awarded digital badges. Digital badges are a graphic verification representing your achievement after completing a specific online course or program.
Admissions
Ready to apply? Learn about taking the next steps.
General Requirements
- Applicants may apply for admission to master’s degree and graduate certificate programs at any time during the year.
- Applicants must have completed an undergraduate degree from a regionally accredited institution and maintained an overall grade point average of 2.75 on a 4.00 scale.
- Applicants must demonstrate the language proficiency necessary for successful graduate coursework.
Prerequisite Coursework and Experience
No prior experience is necessary beyond an undergraduate degree from a regionally accredited institution
GMAT and GRE Exam Scores
GMAT and GRE scores are not required.
Transfer Credits
Transfer credits are not accepted for this program.
English Language Proficiency
Students with transcripts from universities located outside of the United States, unless from a waiver country listed here, are required to take and pass English Proficiency testing.
Saint Mary’s accepts:
- Test of English as a Foreign Language (TOEFL) with a minimum score of 4 (formerly 72)
- International English Language Testing System (IELTS) with a minimum score of 6.0
- Duolingo with a minimum score of 105
- International Test of English Proficiency (ITEP) with a minimum score of 4.0
- Pearson Test of English with a score of 51
- EIKEN with a minimum of Pre-1
- Manchester Exam with a minimum score of 360
Application Requirements
Applicants must submit the following:
1. Completed application form.2. An official transcript(s) issued to Saint Mary’s University of Minnesota from the institution posting the applicant’s completed bachelor’s degree and other relevant transcripts documenting program prerequisites and potential transfer credits. (An official transcript is one that is sent to the university by the credit-granting institution.)
Saint Mary’s can order and cover the cost of transcripts from institutions that allow third-party requests for eligible degree-seeking applicants. Contact your enrollment counselor for more information.
Transcripts from countries other than the U.S. must be evaluated on a course by course basis by a university accepted evaluation service, such as World Education Services, Educational Credential Evaluators, Educational Perspectives, One Earth International Credential Evaluators or any approved member of the National Association of Credential Evaluation Services (NACES.org) and be deemed equivalent to accredited U.S. university standards.
Application Materials should be directed to the Office of Admission
Saint Mary’s University of Minnesota
2500 Park Avenue
Minneapolis, MN 55404
Or electronically: tcadmission@smumn.edu
Application Deadlines
Fall semester term 1 – August 1
Fall semester term 2 – October 1
Spring semester term 1 – December 1
Spring semester term 2 – February 1
Summer semester term 1 – April 1
Summer semester term 2 – June 1
Notice of Acceptance
You can expect to be notified about your acceptance approximately two weeks following your application completion date.
Tuition and Fees
A college education is invaluable. You can take it wherever you want to go or as far as you want to go. The cost of quality education should not get in the way of reaching your goals. Here at Saint Mary’s, we are committed to providing an accessible, quality education that is focused on enhancing your personal and professional growth. Explore cost breakdowns for tuition and other fees of the online Artificial Intelligence certificate.
Graduate Certificate: Artificial Intelligence Careers & Salary
The field of artificial intelligence is growing rapidly along with the expansion of cloud computing, increased use of big data, and prioritization of information security. With the online Artificial Intelligence certificate, you'll gain the AI and programming skills you need for the tech jobs of the future. The salary breakdown of artificial intelligence professionals is:
AI Developer
$77,8501Business Intelligence Architect
$111,5442Data Scientist
$97,4833growth rate is expected for computer and information technology occupations through 2030.4
What You'll Learn
As a graduate of this program, you will be able to:
- Design and deploy an end-to-end AI (artificial intelligence) solution
- Present deliverables to stakeholders that align with an organization’s strategic goals
- Evaluate ethical considerations around artificial intelligence-based solutions
- Consider conflict resolution, cross-functional teamwork, and compliance issues
Frequently Asked Questions
Is this program accredited?
Will my degree say that it is from an online program?
Are there set times when I can start the program?
How long does the program take?
Can I transfer credits from another university and graduate program?
Is there a campus residency requirement, or is the program entirely online?
Will I be required to attend online classes during set times?
Is this a self-paced program?
What are the admissions requirements?
Are there any special technology requirements I need for my coursework?
What type of support is available to me? What if I have a question about homework or need help with a technical issue?
Is financial aid available?
How do I get started?
Sources and Disclaimer
- PayScale, Average AI Programmer Salary, U.S. Retrieved from https://www.payscale.com/research/US/Job=AI_Programmer/Salary.
- PayScale, Average Business Intelligence (BI) Architect Salary, U.S. Retrieved from https://www.payscale.com/research/US/Job=Business_Intelligence_(BI)_Architect/Salary.
- PayScale, Average Data Scientist Salary, U.S. Retrieved from https://www.payscale.com/research/US/Job=Data_Scientist/Salary.
- Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, Computer and Information Technology Occupations. Retrieved from https://www.bls.gov/ooh/computer-and-information-technology/home.htm.
*Completion times may vary
**Students in the BIDA program are required to select an Artificial Intelligence, Business Analytics, or Healthcare Analytics certificate to complete 33 credits to confer a degree.