Securing AI Data and Applications

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Overview

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Secure AI systems and data using enterprise-grade governance, zero-trust architecture, and compliance frameworks. This course teaches you to govern GenAI data safely, implement zero-trust security models, secure applications against evolving threats, and evaluate cloud systems against standards like NIST and SOC 2. You will analyze breach scenarios, design role-based access controls, create infrastructure-as-code policies, and establish secure coding guidelines that prevent vulnerabilities at scale. Build practical skills in incident response, automated policy enforcement, threat modeling, and compliance evaluation. By the end of this course, you will be able to secure AI systems and data confidently, enforce enterprise-grade policies, anticipate and mitigate threats, and demonstrate readiness for senior security roles in AI-driven organizations.

Syllabus

Analyze Data Access Patterns for RBAC Recommendations

You will establish critical skills for securing GenAI data through precise access controls. Learners explore why traditional permission models fail in AI environments, develop expertise in access pattern analysis and function-based RBAC design, and gain hands-on experience using SQL techniques to analyze real access logs.

Evaluate Governance Maturity Against Frameworks

You will transform from framework consumers to assessment practitioners who can lead organizational governance improvement initiatives. Learners gain expertise in DAMA-DMBOK components and advanced assessment techniques, then practice facilitating maturity workshops through screencast demonstrations.

Create Comprehensive Data Stewardship Programs

You will integrate course concepts into practical stewardship program design capabilities. Learners learn the five essential components of effective programs—ownership assignment, quality frameworks, and governance procedures—then develop complete documentation and design skills to transform organizational data governance from ad-hoc practices into systematic capabilities that enable secure, compliant GenAI operations.

Root Cause Analysis for Data Breach Investigation

You will apply investigative techniques using MITRE ATT&CK framework to reconstruct attack timelines, correlate evidence across multiple systems, and distinguish between immediate attack techniques and underlying architectural vulnerabilities requiring systemic remediation.

Zero Trust Architecture Design

You will develop practical zero trust frameworks by implementing identity and access management controls, establishing data loss prevention policies with real-time monitoring, and creating network segmentation strategies that eliminate implicit trust assumptions.

Security Controls Evaluation and Compliance

Learners conduct comprehensive gap analysis comparing current implementations against SOC 2, NIST, and CIS requirements, prioritize remediation activities based on risk impact and compliance criticality, and create executive-ready assessment reports.

Evaluate Security Posture Using Threat Modeling

You will apply systematic security assessment by analyzing threat modeling outputs and penetration testing findings to make informed security decisions for AI systems.

Create Secure Coding Guidelines for Development Teams

You will develop comprehensive secure coding frameworks that bridge security requirements with developer workflow realities, providing actionable guidance that scales across development teams.

Analyze Dependency Vulnerability Reports

You will build proficiency in contextual risk analysis of dependency vulnerabilities, transforming overwhelming vulnerability scan data into actionable remediation plans that protect the organization's most critical assets.

Analyze IAM Audit Logs for Security Anomalies

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

Create Infrastructure-as-Code Security Policies

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

Security Controls Evaluation

You 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.

Project: Securing AI Data and Applications

You will build a comprehensive security governance framework for AI systems by integrating data protection, access control, and compliance evaluation practices. You'll learn how fundamental security components work together to create robust defense systems for AI operations, including how data governance affects access control decisions, how security assessments inform compliance strategies, and how application security prevents system vulnerabilities in real organizational environments.