Goal:
To introduce students to the concepts of DevOps, DevSecOps, MLOps, and MLSecOps, including agile methodologies, cloud platforms, development and operations tools, and automation. The curriculum covers in detail the basic concepts, tools, techniques, principles, challenges, and solutions of DevOps and DevSecOps, including security threats and vulnerabilities. The course introduces students to regulatory frameworks and regulations such as PCI-DSS, HIPAA, and GDPR, the basic concepts, tasks, principles, and levels of MLOps. It covers data and model management, versioning, deployment, MLOps system monitoring, data drift, and concept drift. The course covers automation, scheduling, and scaling in MLOps, AI ethics and security, and MLSecOps principles, challenges, security threats, and vulnerabilities. Finally, the course introduces defense methods and Adversarial Machine Learning techniques, as well as the design of the MLSecOps system.
Course description:
Introduction to DevOps, DevSecOps, MLOps and MLSecOps concepts. Agile methodologies, cloud platforms, development and operational tools, automation. Basic concepts, tools, techniques of DevOps. DevSecOps principles, challenges, solutions, security threats, vulnerabilities. Regulatory frameworks, regulations. Basic concept, task, principles and levels of MLOps. Data and model management, versioning, deployment. MLOps system monitoring, data drift and concept drift. Automation, scheduling and scaling in MLOps. AI ethics and security. MLSecOps principles, challenges, security threats, vulnerabilities. Protection methods, Adversarial Machine Learning techniques. MLSecOps system design.