Curriculum: Artificial Intelligence in Business Graduate Certificate

Next Term Application Deadline

07.01.2025

Total Credits

Next Term Starts

08.25.2025

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Curriculum at a Glance

The Lindner College of Business curriculum for the AI in Business graduate certificate includes four core courses (totaling eight credits) and two elective courses (totaling four credits). View the course options below or in the most updated major map.

CURRICULUM AT A GLANCE

Core Courses Electives

Course	Title / Description	Credit
IS 7065	Generative Artificial Intelligence for Business Course: IS 7065 Credit: 2 This course examines the technology underlying modern generative artificial intelligence / machine learning models from a business perspective, including their uses in coding, professional and artistic applications, and the various controversies and challenges to work and/or society they may pose.	2
BANA 7075	Machine Learning Design for Business Course: BANA 7075 Credit: 2 This course provides a framework for developing real-world machine learning systems that are deployable, reliable, and scalable. Designing machine learning systems is the process of defining the software architecture, infrastructure, algorithms, and data for a machine learning system to satisfy specified business requirements. Without deliberate design, machine learning systems can get outdated quickly because (1) the tools continue to evolve, (2) business requirements change, and (3) data distributions constantly shift. Students will learn about data management, data engineering, feature engineering, approaches to model selection, training, scaling, and how to continually monitor and deploy changes to ML systems for successful business applications. They will also be exposed to managing the human side of ML projects such as team structure and business metrics.	2
IS 7085	Governance of AI/ML Systems Course: IS 7085 Credit: 2 This course teaches students how to develop, scale-up, and sustainably manage high-performing Artificial Intelligence/Machine Learning systems in business organizations. It introduces concepts and techniques that enable the development of surrogate approaches to explain AI/ML models, build redundancy in AI/ML systems, and calculate and minimize risk of failures while using such approaches.	2
IS 8036	Survey of Machine Learning and Artificial Intelligence Course: IS 8036 Credit: 2 This course is a survey of Machine Learning (ML) and Artificial Intelligence (AI) from the Data Scientist’s perspective. It explores ML and AI topics, current and emerging technologies, and applications for students to gain understanding of the successful implementation of ML and AI to address key business and industry problems.	2

Course	Title / Description	Credit
BANA 7025	Data Wrangling Course: BANA 7025 Credit: 2 This course provides an intensive, hands-on introduction to data management and data manipulation. You will learn the fundamental skills required to acquire, munge, transform, manipulate, and visualize data in a computing environment that fosters reproducibility.	2
BANA 7046	Data Mining I Course: BANA 7046 Credit: 2 This is a course in statistical data mining with emphasis on hands-on case study experiences using various data mining/machine learning methods and major software packages to analyze complex real world data. Topics include data preprocessing, k-nearest neighbors, generalized linear regression, subset and LASSO variable selection, model evaluation, cross validation, classification and regression trees.	2
BANA 7047	Data Mining II Course: BANA 7047 Credit: 2 This is a course in statistical data mining with emphasis on hands-on case study experiences using various data mining/machine learning methods and major software packages to analyze complex real world data. Topics include advanced trees: bagging, random forests, boosting; nonparametric smoothing methods; generalized additive models; data preprocessing/scaling; neural networks; deep learning; cluster analysis; association rules.	2
BANA 8090	Special Topics in Business Analytics Course: BANA 8090 Credit: 1-4 This course is used to explore topics of current interest in the BANA domain, that do not fall within the scope of any of the regularly scheduled courses. By the nature of the course, specific topics covered will vary with each offering.	1-4
IS 7036	Data Mining for Business Intelligence Course: IS 7036 Credit: 2 This course is designed for the in-depth learning of data-mining knowledge and techniques in the context of business intelligence. The topics include association rules, classification, clustering and text mining. Students will apply and integrate the business intelligence knowledge learned in this course in leading software packages.	2
IS7088	Artificial Intelligence-Powered Bots Course: IS7088 Credit: 2 This course explores the design, development, and deployment of AI-powered bots, focusing on task automation and conversational AI. Students will learn to automate predefined workflows and gradually incorporate generative AI to enhance bot intelligence and adaptability. Through hands-on projects and case studies, students will gain practical experience in creating AI-powered bots while examining ethical considerations and strategic business impacts.	2
IS 8034	Big Data Integration Course: IS 8034 Credit: 2 This course presents an overview of the principles of data integration, the fundamental basis for developing useful and flexible business intelligence platforms. Modern data integration needs differ from traditional approaches in four main dimensions that parallel differences between big data and traditional data: volume, velocity, variety, and veracity.	2
IS 8070	Special Topics in Information Systems Course: IS 8070 Credit: 1 This course is used to explore topics of current interest in the IS domain, that do not fall within the scope of any of the regularly scheduled courses. By the very nature of the course, specific topics covered will vary with each offering.	1
OM7065	Artificial Intelligence in Healthcare Operations Course: OM7065 Credit: 2 This course explores the transformative role of artificial intelligence (AI) in healthcare, addressing both technical and ethical dimensions. Students will gain an understanding of how AI techniques are revolutionizing patient care, diagnostics, and healthcare management. Through hands-on projects and/or case studies, students will learn to develop, evaluate, and implement AI models tailored to clinical data and healthcare applications. The course will also cover key issues such as data privacy, regulatory frameworks, and the importance of model transparency and fairness in clinical settings. By examining current trends and innovations, including AI in medical imaging, personalized medicine, and public health analytics, students will be equipped to critically assess and contribute to AI advancements that drive better health outcomes. This course is designed for graduate students interested in leveraging AI to address real-world healthcare challenges.	2
OM7085	Artificial Intelligence Applications for Supply Chain Management Course: OM7085 Credit: 2 This course explores how leading firms leverage artificial intelligence (AI) to drive innovation in operations and supply chain management (SCM). The course relies heavily on the case method of instruction. Students will examine AI’s role in the management of operations productivity/efficiency, process management, sourcing/supply management, logistics, and in advancing sustainable practices. Through analysis and discussion of case situations, students will develop a nuanced understanding of how AI shapes modern supply chain management and learn to critically evaluate AI-driven solutions within SCM. By the end of the course, students will be prepared to identify and propose creative use of AI for supply chain decisions and develop a strategic mindset to address the evolving landscape of artificial intelligence as applied to supply chain management.	2
MGMT7019	Artificial Intelligence in Organizations Course: MGMT7019 Credit: 2 This course explores the transformative impact of artificial intelligence (AI) on modern organizations, examining both the opportunities and the challenges that AI presents in the business environment. Students will develop an understanding of AI technologies and their practical applications, while critically analyzing ethical considerations, societal and workforce implications, and strategic implications of AI adoption. The course delves into specific organizational functions, with special emphasis on firm strategy, human resource management, and operational efficiency. Through a combination of theoretical frameworks and real world applications, students will learn to evaluate AI implementation strategies, assess risks, and develop guidelines for responsible AI use in organizations. Students will also gain the knowledge needed to lead AI initiatives, manage human-AI collaboration, and drive innovation in their organizations.	2
MKTG7043	Artificial Intelligence for Marketing Managers Course: MKTG7043 Credit: 2 MKTG 7043 is designed to provide the student with a cohesive understanding of how to use various artificial intelligence platforms across the entire continuum of marketing management through the exploration of marketing problems with an emphasis on qualitative and quantitative analysis, integrative marketing decision-making, and strategy formulation.	2

FAQs

How can this certificate benefit my career?

The AI in Business certificate enhances your skills in leveraging AI for business productivity and problem-solving, making you a valuable asset in a rapidly growing field. You will gain hands-on experience with the latest AI tools, which are highly sought after in today’s job market. Acquiring expertise in AI will position you as a valuable asset to your current or future employers and can lead to career advancement opportunities. The curriculum is designed by experts who are actively working on and researching the latest business applications of AI, ensuring that you are learning the most up-to-date and relevant skills to stay competitive in the job market.

As a student, you will gain access to Lindner’s extensive alumni network of 50,000 professionals, which can provide valuable connections, mentorship, and job placement assistance in this rapidly growing field.

Credits earned in the AI in Business certificate program can be applied towards a Master of Science in Information Systems or a Master of Science in Business Analytics degree. They may also be applied to UC’s MBA, providing a streamlined pathway to further your education and career prospects.
Do I need prior experience with AI tools to enroll?

No prior experience with AI tools is required. However, a basic background in Python programming and information systems is helpful.
How are the classes structured/what is “asynchronous?”

What is asynchronous online learning? Fully asynchronous courses allow you flexibility in your schedule. Once enrolled in a program, you may view instructional materials when it works best for you as long as you meet course deadlines. There is no live video lecture component for this type of learning. For more information on asynchronous learning visit our blog post: Synchronous and Asynchronous Learning

Once enrolled, you’ll use tools like Canvas and meet with your Student Success Coordinator on a regular basis to ensure you’re on track to graduate. Learn more about the UC Online experience in the video below.