Schedule
Business Intelligence runs September 1 - November 1, 2026. Registration closes September 8.
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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.
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
- Understand how business intelligence and data analytics can add value to a company.
- Apply a range of data visualization methods to gain insight into structured data generated by businesses.
- Evaluate clusters of similar datapoints from a dataset to help with market segmentation, inventory management, etc…
- Extract valuable insight from textual data to help with analyzing surveys and customer feedback
- Analyze social networks to capture valuable data and identify actionable business insights
- Apply statistical tests to identify independence among data variables used by businesses.
- Apply data decision trees to help with the prediction of business 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.
Career pathways in business intelligence
Approximate return on investment for each business intelligence and data analyst academic pathway
After successful completion of the online business intelligence course, you can use your newfound data management skills in the workforce or continue your academic career to increase your earning potential. Whether you’re completing a noncredit course or pursuing a bachelor’s degree in business intelligence, learn more about these pathways below and shape your future with MSU Denver.
Pathway 1: Enter the workforce with business intelligence training
Complete the business intelligence online course and enter the workforce with in-demand data management knowledge. Launch your career in data with the core skills needed to become a business intelligence or data analyst. With the growing demand for professionals who can interpret and visualize data, this path offers a strong starting point. The median salary for this pathway is $40,000 per year.
Pathway 2: Continue your academic career in business intelligence
Increase your long-term earning potential and open doors to higher-level data analyst and data-driven leadership roles with a business intelligence degree. Professionals who pursue a business intelligence degree are well-positioned for management and leadership opportunities in data analysis, data reporting, and strategic planning. MSU Denver’s noncredit business intelligence course can also count toward degree requirements, helping you get ahead faster. The median salary for this pathway is $74,680 per year.
Meet your expert business intelligence instructor
Business intelligence instructor
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.
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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