{"id":471,"date":"2026-08-28T04:53:36","date_gmt":"2026-08-28T04:53:36","guid":{"rendered":"https:\/\/sites.wp.odu.edu\/jjcybersec\/?page_id=471"},"modified":"2026-10-10T01:04:57","modified_gmt":"2026-10-10T01:04:57","slug":"cyber-techniques-and-operations-cyse301","status":"publish","type":"page","link":"https:\/\/sites.wp.odu.edu\/jjcybersec\/cyber-techniques-and-operations-cyse301\/","title":{"rendered":"AI Methods and Models (AI410)"},"content":{"rendered":"\n<p>This course introduced me to the foundations of artificial intelligence, from its history and the difference between Narrow AI and General AI to how machines learn and make decisions. Throughout the session, I worked with no-code tools like Teachable Machine to build and analyze machine learning models, then moved into Generative AI, Explainable AI, prompt engineering, and building interactive chatbots. Alongside the technical side, the course also covered the ethical and societal impacts of AI, including bias, misinformation, and fairness. This class taught me that understanding AI means looking at both what it can do and where it falls short, and that using it responsibly requires being able to question its outputs rather than just trust them.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Coursework Artifacts<\/h2>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"wp-block-group__inner-container\">\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-layout-1 wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/sites.wp.odu.edu\/jjcybersec\/basic-linux-commands\/\" target=\"_blank\" rel=\"noreferrer noopener\">Training an Image Classifier with Teachable Machine<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/sites.wp.odu.edu\/jjcybersec\/traffic-tracing-and-sniffing\/\" target=\"_blank\" rel=\"noreferrer noopener\">GenAI and Explainable AI<\/a><\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Reflection<\/h2>\n\n\n\n<p>Throughout this course, I went from using AI as a tool to understanding how it actually works and where it breaks. Each Learning Lab had me approach AI from a different angle. For example, training my own image classifier in Teachable Machine, generating and refining content with GenAI, exploring a model\u2019s behavior with Explainable AI, and practicing prompt engineering on a phishing awareness topic. I tied every lab back to topics in cybersecurity, and because of that,I had to think about how these tools would hold up in real security situations instead of just completing the steps. The biggest challenge was seeing how easily AI can get things wrong, like when my badge classifier mistook anything near the neck for a badge, or when a GenAI response came back far longer than I asked for.<\/p>\n\n\n\n<p>Working through these labs taught me that the quality of what AI produces depends heavily on the data and the prompts behind it. Fixing my classifier showed me that a model can learn shallow patterns like color and position, and refining my prompts showed me that a clear, specific request gets a much better result. Using the What-If Tool also helped me see why transparency matters, since being able to look at why a model made a prediction makes it easier to know when to trust it.<\/p>\n\n\n\n<p>This course changed how I think about AI in cybersecurity. Before, I mostly saw it as a way to automate work and move faster. Now I see it as an assisting tool that still needs human judgment, verification, and clear policies around its use. That connects to my home lab, where I used AI to help triage security alerts, and it will shape how I use AI in future projects. I plan to keep building my technical skills while staying critical of what AI produces instead of just trusting it.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This course introduced me to the foundations of artificial intelligence, from its history and the difference between Narrow AI and General AI to how machines learn and make decisions. Throughout the session, I worked with no-code tools like Teachable Machine to build and analyze machine learning models, then moved into Generative AI, Explainable AI, prompt&#8230; <\/p>\n<div class=\"link-more\"><a href=\"https:\/\/sites.wp.odu.edu\/jjcybersec\/cyber-techniques-and-operations-cyse301\/\">Read More<\/a><\/div>\n","protected":false},"author":27457,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/pages\/471"}],"collection":[{"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/users\/27457"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/comments?post=471"}],"version-history":[{"count":5,"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/pages\/471\/revisions"}],"predecessor-version":[{"id":654,"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/pages\/471\/revisions\/654"}],"wp:attachment":[{"href":"https:\/\/sites.wp.odu.edu\/jjcybersec\/wp-json\/wp\/v2\/media?parent=471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}