Overview
Using AI responsibly and with a reasonable return on investment requires a whole of business commitment. But, understanding AI and Machine Learning can seem beyond the ability of experts in legal, human resources, or marketing. If you don’t know your Kubernetes from your KNN, then the “Fundamentals of AI & Machine Learning” course is a crash course to accelerate your learning about machine learning.
In this session, attendees will be introduced to:
- Essential terminology for machine learning, including terminology for data architecture, data cleaning, algorithmic forms, and machine learning performance metrics,
- Three classic machine learning research papers and will learn how to read these as a well-informed layperson, able to speak more fluently with machine learning team members in your organization.
Session Format
All sessions will take place live and in a virtual setting through 2021 and early 2022. Each will be hosted by knowledgeable FPF experts and carefully selected invited technical experts to provide real-world insights. Sessions are intended to be interactive and registered participants will have an opportunity to ask questions of hosts and to learn from each other.
In-House Corporate Sessions
Sessions are also available for companies as closed, in-house training, using the same curriculum and expert instructors. In-house training allows your teams to ask questions specific to your organization in a non-public format, collaborating and initiating discussions with your internal stakeholders while in the session.
In-house training is provided at a flat fee, per session, and is scheduled at times that are convenient both to your organization and FPF trainers. Sessions are open to your invited employees only (no public admission).
To learn more or to schedule training for your organization, contact us at [email protected].
Cancellation Policy
Cancellations will be honored, minus vendor processing fees, up until 3 days before the scheduled session. For cancellations after that date, we will honor the registration for the next scheduled date of the class or another of the Understanding Digital Data Flows training classes at FPF discretion.