Machine Learning for Business Applications Major

The new major is designed to provide an opportunity to all business majors.  They will gain an understanding of the applied use of data mining, data visualization, and machine learning and artificial intelligence. 

The International Data Corporation ( predicts that data will grow from 33 zettabytes to 175 zettabytes by 2025.  A zettabyte is approximately the size of a trillion gigabytes.  This is a 61% compounded annual growth rate.  Around half of this data will likely live in the cloud.  The numbers are staggering and the implications are huge.  MLBA give analysts the ability to process and find meaning in these extremely large data dets.  MLBA are not only prized skills, but will likely become the most demanded skill for job applicants in the coming years.

Further, the SAS Institute asserts that “…it's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale.”  This helps organizations to be increasingly capable in a highly competitive world, while minimizing unknown risks. (

Learning Goals and Outcomes

  • SLO 1: Students will be able to demonstrate a conceptual and intuitive understanding of the common machine learning algorithms (inc. Supervised and Unsupervised Learning) and when each kind of technique may be appropriate. 
  • SLO 2: Students will be able to define the structure and components of a Python program (using loops, decision statements, functions, and libraries). Additionally, they will be able to work with Python libraries for data processing, and data visualization.  
  • SLO 3: Students will be able to design and implement various machine learning algorithms in a range of business applications. 
  • SLO 4: Students will demonstrate the use of data mining models that can identify hidden patterns and rules.  
  • SLO 5:  Students will be able to communicate clearly and effectively in composing and delivering oral presentations to the target audience.    

The traditional undergraduate programs include 40 courses distributed across three components: A General Education component divided into Signature Courses, Variable Courses, and an Integrative Learning requirement; a Major and Divisional component; and Free Electives. In addition to course requirements as specified in each area, students must complete one certified course in each of the following overlay areas:

  1. Diversity, Globalization or Non-western Area Studies,
  2. Ethics Intensive, and
  3. Writing Intensive. Overlay requirements are part of the forty-course requirement.

General Education Signature Courses

See this page about Signature courses. Six courses

General Education Variable Courses

See this page about Variable courses. Six to Nine courses

General Education Overlays

See this page about Overlays.

General Education Integrative Learning Component

See this page about Integrative Learning Component. Three courses:

Business Foundation 

Ten courses, including:

ACC 101Concepts of Financial Acct.3
ACC 102Managerial Accounting3
DSS 100Excel Competency1
DSS 200Intro to Information Systems3
DSS 210Business Statistics3
DSS 220Business Analytics3
FIN 200Intro to Finance3
or FIN 225 Fund of Quantitative Finance
Essent'ls of Organzational Beh
Essentials of Management
MGT 360Legal Environment of Business3
MKT 201Principles of Marketing3
BUS 495Business Policy4

Major Requirements

DSS 325Open Source Program Lang3
DSS 415Data Wrangling & Visualization3
DSS 420Introduction to Data Mining3
DSS 451AI and ML Business Application3
DSS 455ML Methods in Business3
DSS Elective3