Teaching
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Current course websites
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`MIS 4900/6900 - Advanced Analytics with Python (Summer 2024) `_ - more analytics with Python
`MIS 4460/5460 - Business Analytics (Fall 2024) `_ - spreadsheet based introduction to business analytics
`MIS 4470/5470 - Practical Computing for Data Analytics (Fall 2024) `_ - learn to use R, Python and some Linux to do data analytics work
Permalinks to course websites
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These always contain stable, up to date versions:
- **MIS 4460/5460 - Business Analytics (spreadsheet based)** - `https://mis5460.netlify.app/ `_
- **MIS 4470/5470 - Practical Computing for Data Analytics (R, Python)** - `https://mis5470.netlify.app/ `_
- **MIS 4480/5480 - Advanced Analytics with Python (more Python)** - `https://mis5480.netlify.app/ `_
About courses I teach or have recently taught
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These days I teach mostly upper level business analytics courses. In the past
I've also taught business statistics, simulation, healthcare operations management, and
a number of information systems related courses. You can find links to
current and recent course websites above.
MIS 4460/5460 - Business Analytics
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Spreadsheets are one of the most widely used tools in the business world. They have evolved into a functionally rich platform for quantitative business modeling and decision support system development. This course will allow you to become a power user and developer of spreadsheet based decision support tools for commonly faced managerial decision making problems. You will learn how to conduct "what if?" type analyses, use advanced spreadsheet features such as pivot tables, statistical and financial analysis functions, internal database features, querying external data sources, graphical data display, scenario analysis, risk analysis, simulation, goal seeking and solving optimization problems. You will also learn how to create spreadsheet based decision support tools by using application development features such as Visual Basic for Excel and integrating Excel with other Microsoft Office products such as MS Access. This course will integrate the use of spreadsheets with applied management science topics such as Monte-Carlo simulation and optimization models
MIS 4470/5470 - Practical Computing for Data Analytics
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The overlapping fields of business analytics and data science are getting all kinds of attention in the business world. While trusty tools like Excel spreadsheets and SQL databases are still widely used, there are many other tools wielded by analysts. In this class you will begin to learn how to use R and Python (along with a myriad of companion libraries) to do business analytics work such as:
• accessing large datasets and doing the “wrangling” needed to prepare them for analysis
• managing analytical datasets
• exploratory data analysis and visualization
• build predictive models using statistics and machine learning techniques
• create and manage reproducible analytical processes and workflows
• communicate results and tell stories with data and models
Classes I have taught in the past
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MIS 4450/6450 - Simulation in Business
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Computer simulation is the art and science of creating and using computerized models of real systems to better understand them. Simulation is one of the most important and widely used quantitative/computer modeling techniques used in business. This course is intended to give students the opportunity to be business simulation modelers. Students will become familiar with both the methodology and application of computer simulation modeling within the context of managerial decision making under uncertainty and business process design and analysis. We will use an industry leading discrete event simulation software package called Simio which facilitates construction of dynamic, animated simulation models. Go to the Simio web page and check out some of the video clips to see what this type of simulation modeling is all about.
QMM 241 - Business Statistics II
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
QMM 241 is the second of two quantitative methods courses you will take in the SBA. In QMM 241 we will explore regression, ANOVA, forecasting, and a few other topics. A primary goal of this course is to allow you to start to become a proficient business data analyst. Application and interpretation of statistical concepts will be stressed and much hands-on work will be used to help you learn and use the machinery of statistics in the business world.
QMM 240 - Business Statistics I
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
QMM 240 is the first of two quantitative methods courses you will take in the SBA. In QMM 240 we will cover probability and basic classical statistics (data, data visualization, descriptive statistics, estimation, confidence intervals and hypothesis testing).
`Sample 240 syllabus`_
MIS 100 - Business Problem Solving with Information Technology
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Key computer related skills for surviving as a business student.
MIS 300 - Introduction to Management Information Systems
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Overview of information systems in business.
HCM 540 - Healthcare Operations Management
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
An EMBA course all about operations management in healthcare systems.
.. _Sample 4470/5470 syllabus: http://www.sba.oakland.edu/faculty/isken/syllabi/Syllabus-447680-W17.pdf
.. _Sample 4460/5460 course site: http://www.sba.oakland.edu/faculty/isken/courses/mis5460/
.. _Sample 4450/6450 syllabus: http://www.sba.oakland.edu/faculty/isken/syllabi/Syllabus-Simulation-F14.pdf
.. _Sample 241 syllabus: http://www.sba.oakland.edu/faculty/isken/syllabi/Syllabus-QMM241-W16.pdf
.. _Sample 240 syllabus: http://www.sba.oakland.edu/faculty/isken/syllabi/Syllabus-QMM240-W11.pdf