Learn Business Intelligence Online and Gain Career-Ready Skills

Introduction to Business Intelligence is designed for learners aspiring to enter or upskill in the business intelligence field. This course provides a theoretical foundation in business intelligence and data analytics, distinguishing itself from tool-centric offerings. The course also explores key concepts such as data visualization, text mining, social network analysis, association rules, and predictive modeling techniques.

While practical business applications and management principles are discussed, the emphasis remains on understanding the underlying principles and methodologies that drive business intelligence. Designed with accessibility at the forefront, this business course ensures all students can engage with and apply data analysis concepts, regardless of technical background.

Schedule

Business Intelligence runs September 1 - November 1, 2026. Registration closes September 8.

Format

Self-paced and online, allowing education to fit within your busy schedule. Learners have up to 8 weeks to complete the course.

Cost

$450 per student plus a $35 transaction fee per payment. All learning materials are included with tuition. Group discounts available.

Learning Outcomes

Why Take Business Intelligence?

Professional Career Advisement

Receive a personal advising session with your instructor and gain confidence in your future career.

What students are saying about Business Intelligence*

✓ Increased knowledge, skills, and understanding of the subject matter.

✓ Were highly satisfied with the overall experience of the course.

✓ Agreed that the subject matter was organized and presented effectively.

*Fall 2025 post-course survey results.

 

Meet your expert business intelligence instructor

Business intelligence instructor

Viktor Kiss

Viktor Kiss is a data researcher and educator specializing in business analytics, economic modeling, and complex data systems analysis. Holding a PhD in Business Administration/Economics, his research focuses on modeling complex systems, leveraging advanced statistical and machine learning techniques to analyze economic and business data and dynamics. Kiss has extensive experience teaching business analytics, covering topics such as statistical analysis, data analytics, operations research, and machine learning.

Headshot of a professor wearing a blue shirt and grey blazer

Contact us

Email us

Phone: 303-615-1234

Office Location:
Jordan Student Success Building
3rd Floor – #330
Auraria Campus

Mailing Address:
Metropolitan State University of Denver
Innovative and Lifelong Learning
P.O. Box 173362
Campus Box 6
Denver, CO 80217-3362