W8_L3: MLsecOps скачать в хорошем качестве

W8_L3: MLsecOps

Welcome to Week 8 Lecture 3 of the course "Machine Learning Operations (MLOps)" by Prof. Rangarajan Vasudevan. Full Course: https://study.iitm.ac.in/ds/course_pa... Video Overview This lecture presents a detailed introduction to MLSecOps and explains how security practices can be embedded throughout the entire machine learning lifecycle. As ML systems transition into production environments the need to secure data models and infrastructure becomes crucial. The session outlines the key focus areas for ML security operations and provides a systematic approach to identifying analyzing and mitigating risks across ML pipelines. It includes practical guidance on securing feature store interactions protecting model artifacts implementing continuous vulnerability monitoring and maintaining the integrity confidentiality and availability of production ML services. By mastering MLSecOps principles you will learn how to build ML systems where security is integrated directly into CI CD processes rather than treated as an afterthought. The lecture highlights how scenario planning and threat modeling help anticipate risks such as adversarial attacks data leakage and unauthorized model access. Applying these practices ensures compliance protects sensitive data and significantly reduces operational and regulatory risks in enterprise ML deployments. Key Technical Takeaways Define critical focus areas for end to end ML security operations Learn methodologies for scenario and threat planning specific to ML Understand how to secure feature store access and data flows Develop proactive security checks integrated into CI CD pipelines Chapters 0:00 Introduction to MLSecOps and the Need for Integration 1:45 Defining Focus Areas for ML Security Operations 5:30 Scenario Planning Anticipating Unique ML Threats 10:15 Threat Modeling for Data Pipelines and Model Artifacts 15:00 Best Practices for Security Integration in MLOps About IIT Madras' online Bachelor of Science programme IIT Madras offers four year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/stud... #mlops #mlsecops #mlsecurity #aisecurity #featurestoresecurity #threatmodeling #securityintegration #productionml #datascience #mlengineering #iitmonline