BRANDON, Man. December 13, 2024—Assiniboine College and Palette Skills will partner to deliver an 8-week Digital Agriculture Fundamentals course. This intensive, hybrid upskilling program is designed to introduce mid-career professionals to careers in digital agriculture. “This program will bridge the gap between skills development and industry need,” said Dr. Nicole Gaudette, Dean of the Edwards School at Assiniboine. “Programs like this are align with our goal to offer programs that drive growth, innovation and sustainability within the ag sector. We are grateful to Pallete Skills for the opportunity to expand this program into Manitoba.”
The program will begin on February 3, 2025, with 6 weeks part-time and 2 weeks full-time. Delivered mostly online, the program also includes some in-person sessions. Students will engage in both theoretical learning and practical, hands-on applications. Industry experts will cover emerging technologies such as Geographic Information System (GIS), Internet of Things (IoT), drones, Artificial Intelligence (AI), robotics, and autonomous machinery. Students will also develop a full suite of professional skills including project management, problem-solving, and team-building.
The program aims to prepare highly skilled workers to excel in their field by giving them the tools they need to identify, manage, and implement technological solutions across the agri-food value chain in the Prairies.
“It is a pleasure to be partnering with Assiniboine College and expanding the delivery of our Digital Agriculture Fundamentals program into Manitoba,” said Rhonda Barnet, CEO of Palette Skills. “The skills these participants will be learning are vital for the future of Canadian agriculture, which accounts for one in nine jobs in this country and a big part of Manitoba’s economy.” An online information session for interested applicants will be held on Tuesday, December 17 at 5 p.m. For more information and to register, visit Assiniboine.net/infosessions and look for Digital Agriculture Fundamentals.
