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Online Artificial Intelligence Certificate

Fast facts

Fact 1

Credit Hours

12

Fact 2

Per Credit

$760

Fact 3

Semesters

2

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Program Benefits

  • Digital Badging for all Graduate Certificate Courses
  • Apply Graduate Certificate Credits to an MS BIDA
  • No Prerequisite Courses or GRE/GMAT Required
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HomeOnline ProgramsArtificial Intelligence Certificate

Accelerate Your Career in a Growing Field

Data engineering and artificial intelligence skills are needed in organizations across industries. Learn to use innovative AI skillsets to solve business problems with Saint Mary's University of Minnesota's affordable, 100% online Artificial Intelligence graduate certificate. This certificate is a part of Saint Mary’s Accelerators carefully crafted series of master's-level graduate certificates. Designed to advance your career to help you meet personal and professional goals, this certificate can be taken alone or you can apply your credits as a pathway toward the Master of Science in Business Intelligence and Data Analytics degree program.

Earn a Cutting-Edge Credential in as Few as Five Months

The online Artificial Intelligence graduate certificate is designed for students who are ready for career advancement in the emerging AI field. It explores deep learning, data engineering, and the Internet of Things (IoT) using a hands-on approach. The credits you earn in this certificate program can be applied to our M.S. in Business Intelligence and Data Analytics.*

You will develop valuable skills related to designing data collection methods, programming deep learning models, and working with advanced programming languages and techniques. Because the Artificial Intelligence graduate certificate is delivered in a flexible online format, you can maintain current work commitments and earn a valuable business credential in as few as five months.

*Students in the BIDA program are required to select an Artificial Intelligence, Business Analytics, or Healthcare Analytics certificate to complete 36 credits to confer a degree.

One of the hallmarks of our “accelerators” is that they are stackable into or onto full degree programs. Students can pursue a graduate certificate and then decide to continue into a full degree program in the same or a different discipline.

-Michelle Wieser, Ph.D., Dean of the School of Business and Technology

To learn more about Saint Mary's graduate certificates check out this interview with Michelle Wieser.

Curriculum

The Artificial Intelligence graduate certificate from Saint Mary's 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.

Certificate Courses

Students will be awarded a course-level badge upon the successful completion of each of the graduate course offerings listed below and will also be awarded the graduate certificate badge upon the successful completion of all coursework required for the Accelerator Graduate Certificate

Digital Badging

Now you can share your accomplishments with your professional network using our digital badging for each course completed throughout your course of study in the Artificial Intelligence graduate certificate program. Learn More

Graduate Certificate Artificial Intelligence Saint Mary's University of Minnesota.

BIA 630 Data Analysis and Business Modeling (3 credits)

This course provides an introduction to 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 and complete regression, optimization, and exponential smoothing models.

Upon completion of this course, students are expected to be able to do the following:

  1. Utilize datasets to develop statistics and probability to predict future outcomes.
  2. Implement appropriate models needed to analyze and critically evaluate business objectives.
  3. Develop written and oral communication skills required to report on data-intensive business situations.
  4. Organize data-intensive content in a professional setting.
  5. Execute advanced analytics techniques.

DIGA 620 Data Engineering (3 credits)

The course utilizes 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, as well as 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:

  1. Perform extract, transform, and load (ETL) processes using structured and unstructured data formats.
  2. Assess data for error and implement techniques to improve data integrity.
  3. Determine appropriate data formats for given situations.
  4. Design and document processes for converting raw data into a product suitable for analysis.
  5. Identify legal and ethical issues related to the processing and dissemination of data.

BIA 680 Python for Artificial Intelligence (3 credits)

Prerequisites: BIA 630, DIGA 620

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:

  1. Write high quality, maintainable Python programs for deep learning.
  2. Import Python libraries for artificial intelligence development.
  3. Articulate and demonstrate the value and concepts of Python programming language for analytical modeling.
  4. Apply mathematical operations and code aligned with common machine learning techniques.
  5. Evaluate common approaches to artificial intelligence application development.

BIA 681 Introduction to Deep Learning (3 credits)

Prerequisite: BIA 680

This course introduces students to the complex nature of deep learning. Studying supervised and unsupervised models, students explore the benefits that deep learning offers to businesses. 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:

  1. Communicate a conceptual understanding of why neural networks are gaining popularity.
  2. Compare neural networks with other data structures and the situations in which neural networks should be used over other structures.
  3. Visualize and interpret the components of a shallow neural network.
  4. Construct a basic deep neural network model using Python and the Keras library.
  5. Explain deep neural network model results for stakeholders.

Current Certificate Requirements

For current certificate requirements, visit the Saint Mary's University of Minnesota course catalog.

Program Outcomes

When you complete this program, you will be able to:

  • Design and deploy an end-to-end artificial intelligence-based solution.
  • Present deliverables to prospective stakeholders that align with the strategic goals of an organization.
  • Evaluate ethical considerations around artificial intelligence-based solutions focused on conflict resolution, cross-functional teamwork, and compliance issues.

Prepare for In-Demand AI Careers

The online Artificial Intelligence graduate certificate gives you the AI and programming skills you need for the tech jobs of the future. When you complete your program, you will be qualified for roles such as:

  • AI Developer: $74,293 median annual salary 1
  • Business Intelligence Architect: $112,449 median salary 2
  • Data Scientist: $94,280 median salary 3

Employment in computer and information technology is on the rise and expected to grow 12% through 2028 – much faster than the national average for job outlook.4 Factors like an expansion of cloud computing, the use of big data, and prioritization of information security are all contributing to this impressive growth. As industry need for trained AI professionals continues to increase, our online Artificial Intelligence Certificate puts you on the path to success.

Certificate Completion

The online Artificial Intelligence graduate certificate is designed to be completed in as few as five months and is financial aid eligible. No prerequisite coursework is required, and you don't need GRE/GMAT scores to apply. We recommend that applicants have experience with an object-oriented programming language or SQL databases, and background or previous study of Python is recommended but not required.

For admission to the program, you'll need:

  • An undergraduate degree from a regionally accredited institution
  • A minimum GPA of 2.75 on a 4.0 scale
  • A written statement: Your background and future goals all impact your success with Saint Mary's and inform your education. As you prepare your written statement, think about including previous experiences, education, and your strengths and interests. Share your motivations for earning the online artificial intelligence certification and how it will contribute to your career.
  • The names of two people (including title, organization, email, phone number) who can serve as professional references, if needed, during the application review process. The best references are those who know you in a professional capacity, such as current or former supervisors.
  • A current resume: Include both your educational and professional experience.

If your overall GPA is below 2.75, you may receive conditional status in the program at the discretion of the program director.

For more information about the online Artificial Intelligence graduate certificate, contact us or call 877-308-9954 to speak to an enrollment counselor.

Resources:

1PayScale, Average AI Programmer Salary, U.S. Retrieved from https://www.payscale.com/research/US/Job=AI_Programmer/Salary.

2PayScale, Average Business Intelligence (BI) Architect Salary, U.S. Retrieved from https://www.payscale.com/research/US/Job=Business_Intelligence_(BI)_Architect/Salary.

3Bureau of Labor Statistics, U.S. Department of Labor, Occupational Employment Statistics, Data Scientists and Mathematical Science Occupations, All Other. Retrieved from https://www.bls.gov/oes/current/oes152098.htm.

4Bureau 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.