Online: Tech Quick Learn - Using AI Large Language Models (LLMs)

.00 Points
  • Mon, Jun 16, 2025 - Mon, Jun 16, 2025

  • Online Training

  • Online Training

NON-MEMBERS

$0

MEMBERS

$0

Course unavailable

Contact Information

Details

Course No.

#124401

Category

District: Professional Learning (9431)

Classroom Hours

.00

Non-Classroom
Hours

0

Component Numbers

3.003.006 Technology and Learning

Course Description URL

-

Toggle

Already Started

-

Start Date

Mon, Jun 16, 2025

End Date

Mon, Jun 16, 2025
Session Dates and Times

Registration Deadline

Sat, Jun 14, 2025

Withdrawal Deadline

Sat, Jun 14, 2025

Course Description
 More Details

The Technology Quick Learn sessions explore new methods of using technology, including AI, in teacher's instructional work. In this session, participants will discover the fascinating world of Large Language Models (LLMs) in our engaging training session tailored for K-12 teachers. Gain insights into how LLMs work, their potential applications in education, and best practice considerations.  Participants must attend the 60-minute virtual training and complete a corresponding assignment to be eligible for Inservice credit.
 
Important: Participants must complete a minimum of three, but no more than six, virtual sessions and corresponding assignments to receive Inservice credit. Credit will be awarded in a separate PDS course upon successful completion of all course requirements.


Schedule

START DATE

START TIME

End TIME

06-16-2025

09:00AM

10:00AM

Additional Information


Substitute Provided No
Stipend Provided (Charter teachers) No
Stipend Provided (HCPS teachers) No
Stipend Provided (Private teachers) No
Does this training contribute to a teacher's meeting the criteria for Highly Qualified status? No
Evaluation Method - Students F-Other performance assessment
Evaluation Method - Staff A-Changes in classroom practice
Delivery Methods B-Electronic, Interactive
Follow-Up Methods P-Participant Product related to training (may include lesson plans, written reflection, audio/videotape, case study, samples of student work)