These are courses that I have taught at The University of Iowa.

College of Business Courses

Foundations of Business Analytics (MSCI2800): Analytics is the science of transforming data into insight for better business decision making. This course prepares Tippie College of Business undergraduates for the modern business world in which analytics is a central skill whatever a student’s major and future job. Among the topics discussed in the course are data preparation and data visualization as well as statistical tools such as chi-square testing, regression, and forecasting. In addition, the course will use Microsoft Excel as its central analytics tool. Excel is the most common analytics tool available to professionals, and this course prepares students for its advanced use. This course is online.

Play video 'Course Introduction'View this Course Introduction video (23 minutes.) Button to download transcript SRT file BAUG_Introduction.

 

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.

Play video "Operations Managment Course Introduction" Video Introduction to MSCI3000

 

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.

Play video "Information Systems Course Introduction" Video Introduction to MSCI3005

 

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.

Tableau embbed code web page example.

 

Business Analytics (MBA8150 & MSCI9100) (This course is Quality Matters Certified, 2019): 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.

Course Introduction video (24 minutes.)

Button to play video "Course Introduction" Button to download video "Course Introduction"

Here are two examples of videos from this MBA8150 course.

Ch03 Lecture: Describing Data Numerically (24 minutes)

Button to play video "Ch03 Lecture: Describing Data Numerically" Button to download transcript SRT file Descriptive_Techniques.

Ch03 Excel: Descriptive Statistics (25 minutes)

Button to play video "Ch03 Excel: Descriptive Statistics" Button to download transcript SRT file Excel-Descriptive_Statistics.

 

I taught these courses for the College of Engineering a while ago.

 

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.

Narrative: