AI Explained: Python in Machine Learning Foundations

The application of artificial intelligence (AI), machine learning and deep learning to health care, finance, engineering and many other fields is accelerating expectations for success in business and education.

When you apply AI in various ways, it sparks fresh ideas for designing products, makes factories run smoother, enhances healthcare diagnoses and, in general, makes businesses more cost-effective. This course gives foundational information on machine learning, including insights on primary AI approaches such as expert systems, genetic algorithms and neural networks.

In this hands-on course, we’ll also explore some of the primary software tools available for implementing machine learning, focusing on the Python software language. While Python will be used to work with algorithms and data, prior experience is not required.


Dennis Miller

Dennis Miller

Dennis Miller has a BS and MS in electrical engineering with additional graduate work in computer science. He worked for 35 years for Johnson Controls, Inc. as an engineer and manager in building controls research, product development and software testing. ... read more

Who Should Attend

Data analysts and engineers seeking to understand the uses and implementation of artificial intelligence and machine learning. Prior completion of the Data Analysis Certificate is not required. Participants may choose to take this course on its own or take all courses listed to earn the Data Analysis – Advanced Certificate.

Benefits and Learning Outcomes

  • Gain insight into the primary approaches to AI and the types of business problems to which they can be potentially applied.
  • Experience machine learning, deep learning and some of the primary software tools available for implementation.
  • Explore the importance of quality data to any AI process and some approaches to data analysis and modification for AI use.

Course Outline/Topics

  • Introduction, history and application methods of artificial intelligence (AI)
  • Data requirements for AI methods and data preparation methods
  • Expert systems description and exercises
  • Genetic algorithm description and exercises
  • Artificial neural network description and exercises
  • Examples of applications


Participants should have experience with basic data handling. Prior experience with Python is helpful, but not required.

Date: Tue-Wed, Oct 22-23, 2024

Delivery Method: In-person

Time: Oct 22 8:30am-3:30pm; Oct 23 8:30am-Noon

Location: UWM School of Continuing Education

Instructor: Dennis Miller


$545 by Oct 8, 2024
$575 after Oct 8, 2024

CEUs: 1.0

Enrollment Limit: 20

Program Number: 5020-16222

Registration Deadline: Oct 21, 2024

Register Now

Date: Tue-Thu, May 6-8, 2025

Delivery Method: Live Online

Time: 8:30am-Noon CT

Platform: Zoom

Instructor: Dennis Miller


$545 by Apr 21, 2025
$575 after Apr 21, 2025

CEUs: 1.0

Enrollment Limit: 20

Program Number: 5020-16230

Registration Deadline: May 5, 2025

Register Now


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