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X-ORIGINAL-URL:https://extension.umaine.edu
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DTSTART;TZID=America/New_York:20261109T160000
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DTSTAMP:20261002T192207Z
CREATED:20260925T141118Z
LAST-MODIFIED:20261002T192207Z
UID:10000464-1794240000-1794244500@extension.umaine.edu
SUMMARY:Machine Learning: Intro to AI (Afternoon Sessions)
DESCRIPTION:Monday\, November 9\, 2026\n4:00–5:15 p.m.\nOnline via Zoom\nCost: Free \n Register Online \nNote: This is a 6-session afternoon program meeting Nov. 9 through Dec. 14\, 2026. One registration covers the complete series. Participants must register before the program begins and cannot join after the first session. \nArtificial intelligence (AI) is increasingly part of everyday life. In this six-part online 4-H series\, youth will explore the basics of machine learning through hands-on activities that demonstrate how AI models make predictions\, how models are trained and how beginner computer science concepts work. \nThe series is designed primarily for youth ages 9 to 12\, with teens welcome. No prior experience is required. Participants need access to a computer or tablet and must create a Code.org login. Participants are expected to attend all six sessions. \nSessions will be held from Nov. 9 through Dec. 14: \n\nSession 1: Monday\, Nov. 9\, 4 to 5:15 p.m.\, online via Zoom\nSession 2: Monday\, Nov. 16\, 4 to 5:15 p.m.\, online via Zoom\nSession 3: Monday\, Nov. 23\, 4 to 5:15 p.m.\, online via Zoom\nSession 4: Monday\, Nov. 30\, 4 to 5:15 p.m.\, online via Zoom\nSession 5: Monday\, Dec. 7\, 4 to 5:15 p.m.\, online via Zoom\nSession 6: Monday\, Dec. 14\, 4 to 5:15 p.m.\, online via Zoom\n\nThe series is free\, and donations are welcome. Registration is required by midnight Nov. 1. Space is limited to eight participants\, and a waitlist will be available if the series reaches capacity. \nAn adult or teen volunteer who is comfortable with Zoom and has basic computer science skills is also sought to help lead the series. Contact Sarah Sparks at sarah.sparks@maine.edu for information about volunteering. \nIf reasonable accommodation is needed\, please contact Sarah Sparks\, 207.581.8206\, sarah.sparks@maine.edu by Oct. 26.
URL:https://extension.umaine.edu/event/machine-learning-intro-to-ai-afternoon/
CATEGORIES:Youth Programs
LOCATION:https://extension.umaine.edu/event/machine-learning-intro-to-ai-afternoon/
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DTSTART;TZID=America/New_York:20261109T180000
DTEND;TZID=America/New_York:20261109T191500
DTSTAMP:20260925T144147Z
CREATED:20260925T144003Z
LAST-MODIFIED:20260925T144147Z
UID:10000465-1794247200-1794251700@extension.umaine.edu
SUMMARY:Machine Learning: Intro to AI (Evening Sessions)
DESCRIPTION:Monday\, November 9\, 2026\n6:00–7:15 p.m.\nOnline via Zoom\nCost: Free \n Register Online \nNote: This is a 6-session evening program meeting Nov. 9 through Dec. 14\, 2026. One registration covers the complete series. Participants must register before the program begins and cannot join after the first session. \nArtificial intelligence is part of everyday life\, but how does it work? In this six-part online 4-H series\, youth will explore basic machine learning concepts through hands-on activities using Code.org. Participants will practice making predictions\, training simple AI models and building beginner computer science skills. \nThe series is designed primarily for youth ages 9 to 12\, though teens are welcome. Youth ages 9-18 may participate\, and no prior experience is required. Participants need access to a computer or tablet and must create a Code.org account. Registration covers all six sessions\, and participants are expected to attend each week. \nSessions will be held from Nov. 9 through Dec. 14: \n\nSession 1: Monday\, Nov. 9\, 6 to 7:15 p.m.\, online via Zoom\nSession 2: Monday\, Nov. 16\, 6 to 7:15 p.m.\, online via Zoom\nSession 3: Monday\, Nov. 23\, 6 to 7:15 p.m.\, online via Zoom\nSession 4: Monday\, Nov. 30\, 6 to 7:15 p.m.\, online via Zoom\nSession 5: Monday\, Dec. 7\, 6 to 7:15 p.m.\, online via Zoom\nSession 6: Monday\, Dec. 14\, 6 to 7:15 p.m.\, online via Zoom\n\nThe program is free\, and donations are welcome. Registration closes Nov. 1. Space is limited to eight participants\, with a waitlist available after capacity is reached. \nThe program is also seeking an adult or teen volunteer co-leader who is comfortable with Zoom and has basic computer science skills. Contact Sarah Sparks at sarah.sparks@maine.edu for more information about volunteering. \nIf reasonable accommodation is needed\, please contact Sarah Sparks\, 207.581.8206\, sarah.sparks@maine.edu by Oct. 26.
URL:https://extension.umaine.edu/event/machine-learning-intro-to-ai-evening/
CATEGORIES:Youth Programs
LOCATION:https://extension.umaine.edu/event/machine-learning-intro-to-ai-evening/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261114T100000
DTEND;TZID=America/New_York:20261114T130000
DTSTAMP:20261002T163948Z
CREATED:20261002T163948Z
LAST-MODIFIED:20261002T163948Z
UID:10000470-1794650400-1794661200@extension.umaine.edu
SUMMARY:4-H Science Center Fall Open House
DESCRIPTION:November 14\, 2026\n10 a.m.–1 p.m.\nLafayette and Rawcliffe 4-H Science and Engineering Learning Center\n491 College Avenue\, Orono\, Maine\nCost: Free (registration not required) \nUniversity of Maine Cooperative Extension invites community members to the Fall 4-H Open House on Saturday\, Nov. 14\, from 10 a.m. to 1 p.m. at the Lafayette and Rawcliffe 4-H Science and Engineering Learning Center\, 491 College Ave. in Orono. \nThis free\, drop-in open house will feature hands-on activities for all ages\, including 2D felting\, Maine animal identification\, seed mosaics\, a touch tank and more. Visitors can explore the center\, meet staff and learn about 4-H programs and STEM toolkits. New and returning visitors are welcome. \nIf reasonable accommodation is needed\, please contact Jessy Brainerd\, 207.581.3877\, jessica.brainerd@maine.edu.
URL:https://extension.umaine.edu/event/fall-4-h-open-house/
LOCATION:Lafayette and Rawcliffe 4-H Science and Engineering Learning Center\, 491 College Ave.\, Orono\, ME\, 04473\, United States
CATEGORIES:Community Events
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