Foundations of Artificial Intelligence and Machine Learning (AI/ML)
Upcoming dates (1)
Fee
- $1,975
-
This course has two attendance options, face-to-face or online.
Face-to-face attendance fee includes morning and afternoon breaks, scheduled lunches, and course materials.
Online attendance fee includes online instruction and course materials. Online attendees will access course sessions via the Zoom web conferencing platform.
Discounts
Team 3: When three or more sign up from same employer, your course fee is $1,580.00.
10% discount per person for participants registered in the Technical Leadership Certificate series. Promo code needed during registration.
ID
RA01851-D610
Credits
- CEU: 1.6
- PDH: 16
Schedule
Registration Date/Time:
4/1/2025 7:30am Central Time
Event Dates/Times:
- 4/1/2025 8:00am - 4:00pm Central Time
- 4/2/2025 8:00am - 4:00pm Central Time
- 4/3/2025 8:00am - 12:00pm Central Time
Course Notes
This is a HyFlex (in-person and online) taught course. Your registration is for one teaching platform only: in-person or online. Please be prepared to attend all days either in-person or online. Contact us if you have any questions or if you need to make a change.
Registration confirmation will guide students through accessing the Canvas course site.
Students will create and log in to the Canvas course site with a NetID. Course assets such as instructional materials, participation certificates, and course evaluations will be available to all students through the Canvas course site.
The course materials are all digital and only available on the Canvas course website.
Online attendees will access sessions via the Zoom web conferencing platform. The Zoom link will be provided a few days before the course.
Please watch the email address that you provide during registration for release dates and pre-course information.
Instructor
Barry Vanveen
Location
Cancellation Policy
If you cannot attend, please notify us no later than one week before your course begins, and we will refund your fee. Cancellations received after this date and no-shows are subject to a $150 administrative fee. You may enroll a substitute at any time before the course starts.
Course Overview
Designed for managers, management track, engineers, and technical professionals who need to make decisions about AI/ML related projects and have limited prior experience in AI and machine learning. In this comprehensive course, participants will achieve an understanding of fundamental machine learning concepts, including the advantages and pitfalls of common strategies.
The course will provide the distinction between supervised and unsupervised learning, classification and regression problems, dimension reduction, and clustering challenges. Participants will also gain insights into, data acquisition, data preprocessing/labeling, dataset size, different model types and optimization criteria.
Who Should Attend?
- Engineers
- Scientists
- Managers / Management Track / Management Trainees, Team Leaders & Technical Professionals
- with prior experience in calculus, linear algebra, and statistics.
- with prior experience in calculus, linear algebra, and statistics.
Additional Information
At the completion of this course, participants will be able to:
- Describe advantages and pitfalls in commonly used machine learning strategies.
- Describe considerations in data collection and prep for machine learning
- Explain the differences between commonly used models.
- Describe tradeoffs between dataset size and machine learning model complexity.
- Give examples of optimization criteria for training machine learning models.
- Describe the best practices for using data to both train a machine learning model and predict performance.
- Describe the best practices for optimizing complexity of a machine learning model.
This course is part of the Technical Leadership Certificate. Course may be taken individually as well.
Course Outline
Week 1
Module 1: Introduction to AI & ML Problems
- Data representation and key features of ML pipelines
- Data acquisition and preprocessing example
- Supervised and unsupervised Learning
- Classification and regression problems
- Dimension reduction and clustering problems
- Examples of machine learning approaches
Module 2: Models for Supervised Learning
- Supervised learning review
- Linear models
- Nonlinear models
- Neural network principles
Week 2
Module 3: Training Models and Performance Estimation
- Supervised learning and machine learning models review
- Model selection and performance analysis
- Gradient based optimization methods
- Methods for controlling model overfitting
- Criteria for optimization of classification models
- Multiclass classification criteria
- Backpropagation for training neural networks
Module 4: Clustering and Dimension Reduction
- Unsupervised learning review
- Clustering methods
- Dimensionality reduction, information extraction, and noise reduction
Instructor
Barry Vanveen
Barry D. Van Veen (S’81-M’86-SM’97-F’02) was born in Green Bay, WI. He received the B.S. degree from Michigan Technological University in 1983 and the Ph.D. degree from the University of Colorado in 1986, both in electrical engineering. He was an ONR Fellow while working on the Ph.D. degree.
He has been with the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison since 1987 and is currently Lynn H. Matthias Professor of Electrical and Computer Engineering. His research interests include signal processing for sensor arrays, biomedical applications of signal processing and machine learning, and instructional methods for improving STEM education.
Dr. Van Veen was a recipient of a 1989 Presidential Young Investigator Award from the National Science Foundation and a 1990 IEEE Signal Processing Society Paper Award. He served as an associate editor for the IEEE Transactions on Signal Processing and on the IEEE Signal Processing Society’s Statistical Signal and Array Processing Technical Committee and the Sensor Array and Multichannel Technical Committee. He received the Byron Bird Award for Excellence in a Research Publication from the College of Engineering in 2020.
In recognition of outstanding teaching, Dr. Van Veen received the 1997 Holdridge Teaching Excellence Award from the ECE Department, the 2014 Spangler Award for Technology Enhanced Instruction from the College of Engineering, the 2015 Chancellor’s Distinguished Teaching Award, and the 2017 Benjamin Smith Reynolds Award for Teaching Engineers at the University of Wisconsin. He coauthored “Signals and Systems,” (1st Ed. 1999, 2nd Ed., 2003 Wiley) with Simon Haykin and is the Chief Education Officer at AllSignalProcessing.com, a website devoted to signal processing instruction. Dr. Van Veen is a Fellow of the IEEE.
Foundations of Artificial Intelligence and Machine Learning (AI/ML)
Location: Madison, WI or Live Online
Course #: RA01851-D610
Fee: $1,975
Fee
- $1,975
-
This course has two attendance options, face-to-face or online.
Face-to-face attendance fee includes morning and afternoon breaks, scheduled lunches, and course materials.
Online attendance fee includes online instruction and course materials. Online attendees will access course sessions via the Zoom web conferencing platform.
Discounts
Team 3: When three or more sign up from same employer, your course fee is $1,580.00.
10% discount per person for participants registered in the Technical Leadership Certificate series. Promo code needed during registration.
Credits
- CEU: 1.6
- PDH: 16
Schedule
Registration Date/Time:
4/1/2025 7:30am Central Time
Event Dates/Times:
- 4/1/2025 8:00am - 4:00pm Central Time
- 4/2/2025 8:00am - 4:00pm Central Time
- 4/3/2025 8:00am - 12:00pm Central Time
Course Notes
This is a HyFlex (in-person and online) taught course. Your registration is for one teaching platform only: in-person or online. Please be prepared to attend all days either in-person or online. Contact us if you have any questions or if you need to make a change.
Registration confirmation will guide students through accessing the Canvas course site.
Students will create and log in to the Canvas course site with a NetID. Course assets such as instructional materials, participation certificates, and course evaluations will be available to all students through the Canvas course site.
The course materials are all digital and only available on the Canvas course website.
Online attendees will access sessions via the Zoom web conferencing platform. The Zoom link will be provided a few days before the course.
Please watch the email address that you provide during registration for release dates and pre-course information.
Instructor
Barry Vanveen
Location
Cancellation Policy
If you cannot attend, please notify us no later than one week before your course begins, and we will refund your fee. Cancellations received after this date and no-shows are subject to a $150 administrative fee. You may enroll a substitute at any time before the course starts.
Foundations of Artificial Intelligence and Machine Learning
Course #: RA01851Foundations of Artificial Intelligence and Machine Learning
Date: Tue. October 22, 2024 – Wed. October 30, 2024ID: RA01851-D402
Fee:
- $1,975
-
Online course fee covers course materials and live online instruction.
Team 3: When three or more sign up from same employer, your course fee is $1,580.
10% discount per person for participants registered in the Technical Leadership Certificate series. Promo code needed during registration.
- CEU: 1.6
- PDH: 16
Foundations of Artificial Intelligence and Machine Learning
Date: Wed. April 10, 2024 – Thu. April 18, 2024ID: RA01851-D258
Fee:
- $2,195
-
Fee covers course materials and online Instruction.
10% discount per person for participants registered in the Technical Leadership Certificate series. Discount Code required during registration.
When three or more from the same employer register, the course fee is $1,756 per person.
- CEU: 1.6
- PDH: 16