MLOps Tools (MLflow, Kubeflow) for AI Security Specialists: Securing AI Systems from Novel Threats

Master the integration of MLflow and Kubeflow to build robust, secure MLOps pipelines, safeguarding AI systems against advanced threats like model poisoning, adversarial attacks, and data privacy breaches.

...

Securing the ML Lifecycle with MLflow

Unit 1: MLflow Fundamentals for Security

Unit 2: Threats and Mitigations in MLflow

Unit 3: Securing MLflow Environments

Building Secure MLOps Pipelines with Kubeflow

Unit 1: Kubeflow Fundamentals for Security

Unit 2: Securing Kubeflow Components

Unit 3: Building Secure Kubeflow Pipelines

Unit 4: Advanced Security Practices