Overview

Are you building AI products that need to operate reliably in the real world? Do you want to ensure your AI systems are secure, resilient, and aligned with regulatory expectations?This course is your complete guide to building robust AI products-from concept to continuous improvement.Whether you're an AI product manager, data scientist, tech leader, or ML engineer, this course will equip you with the frameworks and real-world practices to design, deploy, and maintain AI solutions that perform consistently and responsibly.What You'll Learn:How to evaluate data quality, coverage, bias, and robustnessWays to avoid brittle models through smart data and architecture choicesHow to manage risks from AI supply chains, vendors, and third-party modelsTechniques for testing AI across multiple use cases and data scenariosMethods for identifying and defending against prompt injection and adversarial attacksThe principles of AI governance and aligning with GDPR, ISO 27701, and NISTSecure deployment practices and continuous monitoring strategiesHow to build an actionable AI product roadmapEach concept is illustrated using GenAI Assist, a model AI system built by IntelliTech Solutions. This helps you apply lessons directly to real-world use cases in legal, financial, and compliance-focused AI solutions.You'll complete hands-on labs, interactive quizzes, and a final project where you'll create your own Resilient AI Product Roadmap-a practical plan you can apply to any AI project.Who This Course Is For:AI product managers and tech leads seeking real-world deployment strategiesData scientists and ML engineers looking to improve AI reliability and fairnessSecurity professionals involved in AI red teaming and threat mitigationBusiness and compliance leaders responsible for AI accountabilityNo coding required. Whether you're leading AI development or managing its risks, this course helps you deliver AI systems that are trustworthy, scalable, and secure.Join us and start building AI that lasts.

Skills

Reviews