{"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><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>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>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><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>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>This course is delivered by instructors affiliated with Carleton 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>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\n<p><\/p>\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}]}}