Artificial Intelligence and Machine Learning – An Introduction
The application of artificial intelligence (AI), machine learning (ML) and deep learning to enterprises including health care, finance, engineering and many others is an accelerating expectation for business success. When used in one of the many implementation methods, AI results in new ideas for product design, increased factory operation efficiency, improved health care diagnosis, and, in general, more cost-effective business operations. In this course, the primary artificial intelligence methods, expert systems, genetic algorithms and neural networks are described along with the associated data which must be available for their respective implementations. In addition, the deep learning extension of neural networks is explored. Some of the many approaches to software implementation are demonstrated particularly those using the Python software language. This is a hands-on class using Python to work with algorithms and data.
This course can be applied to the following certificates:
Business Administration Certificate
Data Analysis – Advanced Certificate
Python Certificate
Instructor
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
Prerequisites
Participants should have experience with basic data handling. Prior experience with Python is helpful, but not required.
Date: Mon-Wed, June 5-7
Delivery Method: Live Online
Time: 8:30-11:30am CT
Platform: Zoom
Instructor: Dennis Miller
Fee:
$545 by May 22
$575 after May 22
CEUs: 0.9
Enrollment Limit: 15
Program Number: 5020-15003
Note: Participants will receive instructions for logging into Canvas to access course materials and Zoom links several days prior to first session.
Registration Deadline: June 5
Registration is Closed.Date: Tues, Oct 17, 8:30am- 3:30pm CT and Wed, Oct 18, 8:30am-11:30am CT
Delivery Method: In-person
Time: Tues, Oct 17, 8:30am- 3:30pm CT and Wed, Oct 18, 8:30am-11:30am CT
Location: UWM School of Continuing Education
Instructor: Dennis Miller
Fee:
$545 by Oct 3
$575 after Oct 3
CEUs: 0.9
Enrollment Limit: 15
Program Number: 5020-15456
Registration Deadline: Oct 17
Date: Mon-Wed, June 10-12, 2024
Delivery Method: Live Online
Time: 8:30-11:30am CT
Platform: Canvas
Instructor: Dennis Miller
Fee:
$545 by May 27, 2024
$575 after May 27, 2024
CEUs: 0.9
Enrollment Limit: 15
Program Number: 5020-15461
Registration Deadline: June 10, 2024
