Full course description
In today’s digital age, all industries depend on data-driven analytical models to analyze historical trends/patterns, improve processes, predict future outcomes, optimize strategies, and uncover business intelligence. Business analytics (BA), a set of methods, tools, and approaches companies use, is one of the most in-demand skills in today’s workforce. It allows a company to gain a competitive advantage, minimize operational costs, and improve customer satisfaction. The demand for professionals with a data analytics skillset remained strong even during the economic disruptions and workforce downsizing caused by the COVID-19 global pandemic. Besides, the BA-related job opportunities are expected to flourish, as the US Bureau of Labor Statistics estimates over 30% growth, one of the highest, during the next 10 years. Currently, there exists a shortage in the supply of professionals with the necessary analytics skills. This course introduces the core principles, methods, and tools associated with data analytics and provides hands-on training in using popular analytical tools. The course covers advanced tools/techniques for data summarization, visualization, predictive modeling, association mining, clustering, and natural language processing. It is organized around the two foundational pillars of data analytics – descriptive analytics and predictive analytics. This course is based around the idea of active and experiential learning, where students learn the concepts and techniques by participating and engaging in various activities such as hands-on problem solving, tutorials, and case studies.
Note: This course is part of the Digital Transformation Certificate Program that offers three online courses available through MU Extension and Engagement: Business Data Analytics, Coding and Programming, and Geographical Information Systems. Individuals will receive a certificate of completion for each completed course, and those who complete all three courses will receive an MU Extension Continuing Education Certificate in Digital Technology.
The following objectives are for this six-week course. Each assessment will have a list of objectives that are in line with the following. Students who complete this course will be able to:
- Understand the fundamentals of data analytics and its practical applications.
- Gain quantitative problem-solving skills applicable to any industry (e.g., healthcare, manufacturing, transportation/logistics, etc.).
- Develop and deploy state-of-the-art analytical tools for optimizing operational costs, business process efficiency, and service quality.
- Derive data-driven business intelligence.
Module 1: Foundation of Business Analytics
Module 2: Exploratory Analysis and Visualization
Module 3: Overview of Predictive Analytics
Module 4: Supervised Machine Learning
Module 5: Unsupervised Machine Learning
Module 6: Course Wrap-up
Dr. Sharan Srinivas and Dr. Kangwon Seo
Department of Industrial and Manufacturing Systems Engineering
MU Extension Support Staff for Enrollment Questions:
Sarah Rielley: firstname.lastname@example.org
Jonathan Mack: email@example.com
MU College of Engineering