Packt

Designing Secure AI Architectures for Modern Systems

Packt

Designing Secure AI Architectures for Modern Systems

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Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Analyze AI attack surfaces across models, endpoints, and APIs

  • Design zero trust pipelines for secure AI system deployment

  • Implement prompt firewalls and token-level filtering controls

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Recently updated!

September 2026

Assessments

7 assignments

Taught in English

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There are 8 modules in this course

This module provides an overview of the course structure, key themes, and learning goals. Learners will gain foundational knowledge on designing secure AI architectures for modern systems. It sets the stage for understanding the importance of security in AI development.

What's included

1 video

This module covers the critical security challenges in AI infrastructure, including protecting model weights, securing inference endpoints, and mitigating various attack vectors. Learners will gain insights into data privacy, threat detection, and secure AI deployment strategies. It also explores how to implement and assess security measures in real-world AI systems.

What's included

14 videos1 assignment

This module explores critical strategies for building secure AI systems, including input filtering, data protection, and system integrity measures. Learners will gain practical knowledge on implementing defensive techniques to prevent security vulnerabilities and maintain ethical AI operations.

What's included

8 videos1 assignment

This module explores key concepts in AI governance, including risk classification, transparency reporting, and documentation practices. Learners will gain insights into managing AI systems responsibly and ensuring compliance with evolving regulatory standards.

What's included

6 videos1 assignment

This module explores strategies for managing AI autonomy and tool access, focusing on risk mitigation, command interpretation, and approval processes. Learners will gain insights into defining permissions, limiting AI actions, and implementing safe decision-making frameworks.

What's included

4 videos1 assignment

This module covers strategies for securing AI systems through vulnerability scanning, dataset tracking, and cross-team collaboration. It also explores how to position security as a business asset and addresses key threats and defenses in AI model security.

What's included

4 videos1 assignment

This module covers key strategies for securing AI systems in cloud environments, including private networking, access control, and compliance with data residency requirements. Learners will gain an understanding of how to implement and manage security measures for enterprise-level AI deployments.

What's included

8 videos1 assignment

This module explores critical strategies for managing identity and access in multi-cloud environments, secure API gateway configurations, and data encryption practices. Learners will gain insights into protecting data across cloud platforms and implementing secure, scalable solutions.

What's included

3 videos1 assignment

Instructor

Packt - Course Instructors
Packt
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