{"id":33423,"date":"2026-06-30T11:45:21","date_gmt":"2026-06-30T15:45:21","guid":{"rendered":"https:\/\/carleton.ca\/geography\/?page_id=33423"},"modified":"2026-06-30T11:45:21","modified_gmt":"2026-06-30T15:45:21","slug":"geoai-mini-course","status":"publish","type":"page","link":"https:\/\/carleton.ca\/geography\/geoai-mini-course\/","title":{"rendered":"GeoAI Mini Course"},"content":{"rendered":"\n<section class=\"w-screen px-6 cu-section cu-section--white ml-offset-center md:px-8 lg:px-14\">\n    <div class=\"space-y-6 cu-max-w-child-5xl  md:space-y-10 cu-prose-first-last\">\n\n            <div class=\"cu-textmedia flex flex-col lg:flex-row mx-auto gap-6 md:gap-10 my-6 md:my-12 first:mt-0 max-w-5xl\">\n        <div class=\"justify-start cu-textmedia-content cu-prose-first-last\" style=\"flex: 0 0 100%;\">\n            <header class=\"font-light prose-xl cu-pageheader md:prose-2xl cu-component-updated cu-prose-first-last\">\n                                    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 relative after:absolute after:h-px after:bottom-0 after:bg-cu-red after:left-px text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] pb-5 after:w-10 text-cu-black-700 not-prose\">\n                        GeoAI: Introduction to Deep Learning with Geospatial Data\n                    <\/h1>\n                \n                                \n                                    \n\n<p class=\"wp-block-paragraph\"><strong><br><\/strong>Transform how you use geospatial data with Machine Learning (ML) &amp; Artificial Intelligence (AI). Most AI courses overlook the complexities of spatial data. This course focuses on practical geospatial workflows you can use in research and industry.<\/p>\n\n\n                            <\/header>\n\n                    <\/div>\n\n            <\/div>\n\n    <\/div>\n<\/section>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"559\" src=\"https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image-1024x559.png\" alt=\"GeoAI mini course\" class=\"wp-image-33424\" srcset=\"https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image-1024x559.png 1024w, https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image-512x279.png 512w, https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image-320x175.png 320w, https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image-768x419.png 768w, https:\/\/carleton.ca\/geography\/wp-content\/uploads\/sites\/108\/2026\/06\/GeoAI_image.png 1408w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h6 id=\"course-details\" class=\"wp-block-heading\">COURSE DETAILS<\/h6>\n\n\n\n<p class=\"wp-block-paragraph\">Dates: August 10\u201314, 2026<br>Format: Online (live + guided hands-on)<br>Time: 11:00 AM \u2013 4:00 PM (ET)<br><br><strong class=\"myprefix-text-bold\">DAILY STRUCTURE<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>11:00 \u2013 2:00 \u2192 Concepts, guided exercises, discussion<\/li>\n\n\n\n<li>2:00 \u2013 4:00 \u2192 Independent hands-on (with support)<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Follow-up session: August 19 (1-hour Q&amp;A)<\/p>\n\n\n\n<h6 id=\"who-should-attend\" class=\"wp-block-heading\">WHO SHOULD ATTEND<\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>GIS \/ Remote sensing professionals<\/li>\n\n\n\n<li>Environmental professionals <\/li>\n\n\n\n<li>Graduate students (Geomatics, Geography, Environmental Science, related disciplines)<\/li>\n\n\n\n<li>Researchers &amp; postdocs<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Note: Basic understanding of remote sensing is expected<\/em><\/p>\n\n\n\n<h6 id=\"what-you-will-learn\" class=\"wp-block-heading\">WHAT YOU WILL LEARN<\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>How to optimize and tune machine learning and neural network models for different earth observation studies.<\/li>\n\n\n\n<li>How to handle spatially auto-correlated data with machine learning models.<\/li>\n\n\n\n<li>What are different neural network types and how can you use them with earth observation data.<\/li>\n\n\n\n<li>How to use data from foundation models in order to create earth observation products.<\/li>\n<\/ul>\n\n\n\n<h6 id=\"course-outline\" class=\"wp-block-heading\">COURSE OUTLINE<\/h6>\n\n\n\n<p class=\"wp-block-paragraph\">Day 1: Spatial Autocorrelation &amp; Sampling Design<br>Day 2: Data Types, Parameter Tuning, &amp; Cross-Validation<br>Day 3: An Introduction to Neural Networks<br>Day 4: Gradient Descent Optimization<br>Day 5: Convolutional Neural Networks &amp; Foundation Models<\/p>\n\n\n\n<h6 id=\"instructors\" class=\"wp-block-heading\">INSTRUCTOR(S)<\/h6>\n\n\n\n<p class=\"wp-block-paragraph\">This course is delivered by instructors affiliated with ÐÓ°ÉÔ­´´ University, the University of Ottawa, Natural Resources Canada (NRCan), and partner organizations. Instructors bring expertise in GeoAI, remote sensing, and geospatial technologies, combining academic research with hands-on experience in real-world geospatial and environmental applications.<\/p>\n\n\n\n<h6 id=\"fees-registration\" class=\"wp-block-heading\">FEES &amp; REGISTRATION<\/h6>\n\n\n\n<p class=\"wp-block-paragraph\">Regular: C$750<br>Student pricing (open to all institutions): C$250 (limited spots)<br><br><a href=\"https:\/\/payments.carleton.ca\/geography\/geoai-introduction-to-deep-learning-with-geospatial-data-august-2026\/\">Registration link<\/a> (click to the left to register)<br>Deadline: August 7, 2026<br>Contact: Ashraf Elshorbagy (<a href=\"mailto:ashraf.elshorbagy@carleton.ca\">ashraf.elshorbagy@carleton.ca<\/a>)<\/p>\n\n\n\n<h6 id=\"why-this-course\" class=\"wp-block-heading\">WHY THIS COURSE?<\/h6>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Built specifically for geospatial and environmental workflows<\/li>\n\n\n\n<li>Strong balance of theory and hands-on practice<\/li>\n\n\n\n<li>Focus on real-world applications, not generic AI<\/li>\n\n\n\n<li>Designed for both academia and industry<\/li>\n<\/ul>\n\n\n","protected":false},"excerpt":{"rendered":"<p>COURSE DETAILS Dates: August 10\u201314, 2026Format: Online (live + guided hands-on)Time: 11:00 AM \u2013 4:00 PM (ET) DAILY STRUCTURE Follow-up session: August 19 (1-hour Q&amp;A) WHO SHOULD ATTEND Note: Basic understanding of remote sensing is expected WHAT YOU WILL LEARN COURSE OUTLINE Day 1: Spatial Autocorrelation &amp; Sampling DesignDay 2: Data Types, Parameter Tuning, &amp; [&hellip;]<\/p>\n","protected":false},"author":632,"featured_media":33424,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_cu_dining_location_slug":"","footnotes":"","_links_to":"","_links_to_target":""},"cu_page_type":[],"class_list":["post-33423","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":{"cu_post_thumbnail":""},"_links":{"self":[{"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/pages\/33423","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/users\/632"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/comments?post=33423"}],"version-history":[{"count":5,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/pages\/33423\/revisions"}],"predecessor-version":[{"id":33439,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/pages\/33423\/revisions\/33439"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/media\/33424"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/media?parent=33423"}],"wp:term":[{"taxonomy":"cu_page_type","embeddable":true,"href":"https:\/\/carleton.ca\/geography\/wp-json\/wp\/v2\/cu_page_type?post=33423"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}