These are courses that I have taught at The University of Iowa.
Business Analytics (MSCI2800): This course is under development. Introduction to business decision making using data; students transform data into Insight using visualization, statistics, and optimization; introduction to Excel as a tool for business analytics. This course is online.
Operations Management (MSCI3000): Strategic, tactical, operational issues that arise in management of production and service operations; product and process design, facilities planning, quality management, materials management, operations planning and scheduling, emerging technologies in production and service management. This course is online.
Information Systems (MSCI3005): Application of computing principles to solving business problems; information technology in modern organizations; focus on sound data analysis to support decision making; tools used for problem solving (spreadsheets, databases, web applications); role of information systems in organizations; components of information technology; Internet and network economy; basic data analysis and visualization; decision‑making logic represented as algorithms; perform what‑if analysis with data; emerging technologies. This course is online.
Data Management and Visual Analytics (MSCI6050): Understanding how data is stored in databases and learning the tools used to access the data is key to creating datasets used to answer many business questions; how to manage and access data in relational databases using Structured Query Language (SQL); basic principles of visual analytics and techniques for presenting data retrieved from databases.
Rick's Tableau Public - Display of some visualizations.
Business Analytics (MBA8150 & MSCI9100): Introduction to analytical techniques for making business decisions; utilizing Excel to apply descriptive and predictive analytical tools to solve practical business problems using real world data; dealing with uncertainty in decision making; formal probability concepts and statistical methods for describing variability (decision trees, random variables, hypothesis testing); application of techniques (linear regression, Monte Carlo simulation, linear optimization) to model, explain, and predict for operational, tactical, and strategic decisions. This course is both in-class and online.
Design for Manufacture (DFM): This course provides students with the opportunity to develop and demonstrate an understanding of product design, engineering graphics, and manufacturing processes fundamentals.
Robotics: Operation and control of robot systems; robotic sensors and data acquisition subsystems; machine vision; software for robot control; design of robotic workcells; laboratory projects.
These last two syllabi are courses that I have taught several years ago, their syllabi may appear a little strange because of the web editor that I had used to create them.
Miscellaneous: Just what the name implies.