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Build AI applications that are not only powerful, but secure by design.In this hands-on AI Security Masterclass, you will learn how to build, attack, and secure modern applications powered by Large Language Models (LLMs). Using Python and Ollama, you will create a complete AI assistant and progressively add chat, Retrieval-Augmented Generation (RAG), tool calling, persistent memory, autonomous agents, and production security controls.You will begin by building a local AI chat assistant and exploring why LLM security differs from traditional application security. You will then launch realistic prompt injection attacks, attempt to expose hidden instructions, test role-playing and multi-turn jailbreaks, and experiment with encoded prompt manipulation techniques.Next, you will build a document-based RAG application capable of answering questions from PDFs. You will see how malicious documents can introduce indirect prompt injection, poison retrieved context, manipulate answers, and undermine trusted knowledge. You will secure the RAG pipeline using source validation, context isolation, sanitization, and enforcement controls.The course then moves beyond chatbot responses into real application actions. You will build a tool-calling AI assistant with weather, calculator, and email tools. You will test parameter injection and unauthorized tool execution before implementing input validation, least-privilege permissions, destination restrictions, and human-in-the-loop approval for sensitive actions.You will also add persistent AI memory and learn how attackers can poison stored information to manipulate future conversations. You will protect memory using validation, approval workflows, risk scoring, and safe storage policies.As the assistant becomes more autonomous, you will build an AI agent capable of planning tasks, selecting tools, and executing multi-step workflows. You will then attempt to compromise its decisions and secure it with permissions, policy enforcement, approval gates, and constrained execution.By the end of the course, you will combine every defense into a reusable AI Security Gateway that includes:Prompt injection detectionJailbreak filtering and risk scoringRAG security and context sanitizationTool authorization and parameter validationMemory poisoning protectionAgent security controlsHuman approval workflowsOutput validation and audit loggingFinally, you will package and run the complete secure AI assistant using Docker and connect it to local models through Ollama.This course is ideal for Python developers, Generative AI engineers, RAG developers, AI agent builders, software engineers, and technical professionals who want practical experience securing real LLM applications.You will not simply study AI attacks. You will build vulnerable features, exploit them, implement defenses, and verify that those defenses work.Build it. Attack it. Secure it.
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This comprehensive free online course on Udemy covers everything you need to become proficient in AI application security. Whether you're a beginner or looking to advance your skills, this free Udemy course with certificate provides hands-on training and practical knowledge you can apply immediately.
This free certification course is perfect for anyone looking to break into AI development or enhance their existing skills. Here's who will benefit most from this no-cost training opportunity:
Learn from Arjun Vaid and School of AI, experienced professionals in AI security and development. Arjun, a seasoned developer with 15+ years building enterprise applications, brings proven attack/defend methodologies from real-world deployments. School of AI combines structured curricula with collaborative learning communities that empower technical professionals.
With 11 comprehensive lessons[video_hours if >0: and X hours of video tutorials], this free online course taught in English stands out through its offensive-defensive training approach. What makes this free Udemy course unique is its hands-on build-hack-secure methodology that guarantees practical mastery. Upon completion, you'll receive a certificate to showcase on LinkedIn and your resume. Plus, with mobile access, you can learn anytime anywhereโperfect for busy professionals.
Follow these simple steps to claim your free enrollment:
โ ๏ธ Important: This free Udemy coupon code expires on [human-readable date]. The course will return to its regular $84.99 price after this date, so enroll now while it's completely free. This is a legitimate working couponโno credit card required, no hidden fees, no trial periods. Once enrolled, the course is yours forever.
Here's why this free certification course is an opportunity you can't afford to miss: 1) Learn critical AI security skills that prevent $7.8B annual LLM breaches 2) Build marketable expertise in prompt injection defense and RAG security 3) Create portfolio projects using Docker and Ollama 4) Access regular content updates with lifetime enrollment
Yes! By using our exclusive coupon code JULFREE02, you get 100% off the regular price. This makes the entire course completely freeโno payment required, no trial period, and no hidden costs. You'll have full access to all course materials just like paying students.
This limited-time offer expires on [human-readable date]. After this date, the course returns to its regular $84.99 price. We highly recommend enrolling immediately to secure your free access. The coupon has limited redemptions available.
Absolutely! Upon completing all course requirements, you'll receive an official Udemy certificate of completion. This certificate can be downloaded, shared on LinkedIn, and added to your resume to showcase your new skills to employers.
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Once you enroll using the free coupon code, you get lifetime access to all course materials. There's no time limitโlearn at your own pace, revisit lessons anytime, and benefit from future updates at no additional cost. Your one-time free enrollment gives you permanent access.
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Upon completion of all video lectures, Udemy will issue a certificate of completion.
Once you enroll with the coupon, you get full lifetime access to the materials.


