Building AI Products: Security Essentials Professional Certificate by LinkedIn Learning

Overview

Artificial intelligence demands robust security safeguards to protect against emerging threats. These courses teach critical AI security skills including data governance, secure architecture, incident response, and comprehensive testing methodologies.

You'll gain the expertise needed to build and maintain secure AI products in today's complex technology landscape. Tune in, pass the final exam, and earn your certificate.Implement data security frameworks for AI product protection.Identify security vulnerabilities in AI system architecture.Analyze AI security incidents for effective response.Develop comprehensive test plans for AI system validation.

Syllabus

• Course Introduction
Overview of AI Security
Importance of Security in AI Products
Course Goals and Objectives
• Module 1: Data Governance in AI
Understanding Data Governance Frameworks
Implementing Data Security Frameworks
Best Practices for Data Management in AI
• Module 2: Secure AI Architecture
Fundamentals of Secure Architecture Design
Identifying Security Vulnerabilities in AI Systems
Strategies for Securing AI Pipelines
• Module 3: Incident Response in AI Systems
Introduction to AI Security Incidents
Analyzing and Responding to AI Security Breaches
Building an Effective Incident Response Plan
• Module 4: Testing and Validation of AI Systems
Developing Comprehensive Test Plans
Testing Methodologies for AI Security
Tools and Techniques for AI System Validation
• Module 5: Implementing Security Safeguards
Developing Security Policies and Procedures
Enhancing AI Security Posture
Case Studies in AI Security Implementation
• Final Exam and Certification
Exam Preparation and Guidelines
Completing the Final Exam
Earning the Security Essentials Professional Certificate
• Course Wrap-up
Reviewing Key Learnings
Further Resources and Next Steps

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Taught by

Meghan Maneval, Sam Sehgal and Malcolm Shore

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Subjects

Computer Science