What does cloud security governance mean in this course?

In this course, cloud security governance means using a structured way to monitor access activity, enforce security rules in infrastructure, and check controls against recognized standards. The focus is on making security repeatable across cloud environments instead of treating it as a one-time review.

When would you use cloud security governance in practice?

You would use this approach when you need to investigate unusual permission changes, block insecure infrastructure changes before deployment, or assess whether current controls meet compliance expectations. The course places it in everyday cloud operations where access, configuration, and evidence all need regular review.

How does cloud security governance fit into a broader workflow?

It fits between routine cloud administration and formal audit work by connecting monitoring, policy enforcement, and control review into one repeatable process. In the course, that means moving from isolated checks toward a broader workflow for investigation, prevention, and evaluation.

How is cloud security governance different from reactive incident response?

Reactive incident response begins after a problem is already in motion, while cloud security governance also focuses on preventing issues and checking controls continuously. Here, the emphasis is not only on handling alerts but on using baselines, automated policies, and reviews to catch weaknesses earlier.

Do you need any prerequisites before learning cloud security governance?

A basic background in cloud infrastructure, core security concepts, and familiarity with infrastructure-as-code tools is helpful before starting. Because the course is intermediate, it assumes you can follow how permissions, configuration changes, and policy checks relate to one another.

What tools, platforms, or methods are used in this course?

Learners work with IAM audit logs and policy-as-code approaches in deployment pipelines. Compliance frameworks such as SOC 2 and NIST are then used to evaluate whether those controls are working as intended.

What specific tasks will you practice or complete in this course?

You practice analyzing access logs for suspicious privilege changes, creating security policies that enforce encryption and network segmentation, and mapping existing controls to compliance requirements. You also document evidence and gaps so the overall governance process supports investigation, prevention, and ongoing evaluation.

Analyze, Create, and Evaluate Cloud Security

本课程是 AI Systems Reliability & Security 专项课程的一部分

位教师：Hurix Digital

包含在中

了解更多

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Security monitoring relies on clear behavioral baselines to separate normal admin activity from anomalies that may signal security threats.
Infrastructure-as-code enables proactive security governance, preventing vulnerabilities at scale more effectively than reactive incident response.
Compliance frameworks support structured risk management and must be continuously reviewed to adapt to evolving security threats.
Automated policy enforcement in CI/CD pipelines builds scalable, sustainable security practices that grow with the organization.

您将获得的技能

您将学习的工具

AWS Identity and Access Management (IAM)

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 AI Systems Reliability & Security 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有3个模块

Master the critical skills for securing cloud infrastructure through systematic analysis, proactive policy creation, and comprehensive compliance evaluation. This course empowers you to become a guardian of cloud security by teaching you to detect suspicious privilege escalations in IAM audit logs, automate security governance through infrastructure-as-code policies, and assess organizational controls against industry standards like SOC 2 and NIST.

This Short Course was created to help Machine Learning and Artificial Intelligence professionals accomplish robust cloud security governance that scales with enterprise demands. By completing this course, you'll be able to investigate security incidents with precision, prevent vulnerabilities through automated policy enforcement, and demonstrate compliance readiness that builds stakeholder confidence. By the end of this course, you will be able to: • Analyze IAM audit logs to detect anomalous privilege escalations • Create infrastructure-as-code policies to enforce encryption and network segmentation • Evaluate security controls and practices against industry standards and compliance requirements This course is unique because it bridges the gap between security theory and practical implementation, teaching you to think like both a security investigator and a proactive system architect. To be successful in this project, you should have a background in cloud infrastructure, basic security concepts, and familiarity with Infrastructure-as-Code tools.

单元详情

Learners will master the critical skill of detecting security threats through systematic IAM audit log analysis, enabling them to protect cloud infrastructure from privilege escalation attacks.

涵盖的内容

3个视频1篇阅读材料1个作业

Learners will develop the critical skill of embedding security requirements directly into infrastructure deployment processes, ensuring consistent policy enforcement at scale.

涵盖的内容

3个视频2篇阅读材料2个作业

3个视频总计16分钟

The Hidden Cost of Security Vulnerabilities in Production3分钟
OPA and Terraform Policy Implementation Strategies7分钟
Building OPA Policies for Kubernetes Security Enforcement5分钟

2篇阅读材料总计18分钟

Policy-as-Code Fundamentals and Security Automation10分钟
Encryption and Network Segmentation Policy Patterns8分钟

2个作业总计15分钟

Create Encryption and Network Segmentation Policies12分钟
Automating Encryption and Network Segmentation with Infrastructure-as-Code Policies3分钟

Learners will develop comprehensive skills in security controls evaluation by systematically assessing organizational security practices against industry standards like SOC 2 and NIST, identifying compliance gaps, and ensuring regulatory adherence for AI/ML environments.