AI-SECURITY · 4 WEEKS · 48 LESSONS
Responsible AI and Security on AWS: Building Secure and Ethical AI Systems
Implement secure and responsible AI systems on AWS using industry best practices for security, monitoring, and ethical AI development
Master AWS AI security and responsible AI practices through comprehensive coverage of security architectures, monitoring systems, and ethical implementations. Learn to implement robust security controls with CloudTrail integration, Bedrock guardrails, and advanced security boundaries. This course covers essential topics from authentication patterns to SageMaker Clarify, providing hands-on experience in building secure, responsible AI systems while implementing industry best practices for AI security and ethics.
01 — What learners say
Real feedback from real learners.
“The Rust Fundamentals course was fantastic for formalizing my base Rust knowledge. It was well-paced for both beginner and experienced developers.”
“The course was incredibly informative and well-structured. I gained practical skills that immediately applied in my work, making it a highly valuable learning experience.”
“The course on AI Fundamentals is not only engaging but also practical. Having worked with AWS before, the way it explained Azure cncepts made switching seamless and easy to grasp.”
“I can say that it's a great series of courses for those who are looking to practical MLOps knowledge.”
“This course got clear videos, exercises, and questions, and there are extra resources too. When you're done, you'll have a solid foundation to dive into topics like DevOps or ML.”
02 — Why this course
What you'll walk away with.
Master AWS AI security and responsible AI practices through comprehensive coverage of security architectures, monitoring systems, and ethical implementations. Learn to implement robust security controls with CloudTrail integration, Bedrock guardrails, and advanced security boundaries. This course covers essential topics from authentication patterns to SageMaker Clarify, providing hands-on experience in building secure, responsible AI systems while implementing industry best practices for AI security and ethics.
Design and implement secure AI architectures on AWS
Deploy comprehensive monitoring and logging systems for AI applications
Implement CloudTrail integration for Bedrock security monitoring
Master Bedrock guardrails for input validation and output safety
03 — Syllabus
4 weeks, 48 lessons total.
- Course introduction
- Ai security architecture
- Ai AUTH patterns
- Key terms
- Lab
- Quiz
- Cloudtrail flow for Bedrock
- Cloudtrail Visualization for Bedrock
- Key terms
- Lab
- Quiz
- Reflection
- Bedrock Guardrails security boundaries notes
- Edge cases diagram Guardrails
- Key terms
- Lab
- Quiz
- Reflection
- Responsible AI with Sagemaker Clarify
- Key terms
- Lab
- Quiz
- Reflection
- Course conclusion
04 — For teams
Custom training for your company.
We're ready to deliver this and other courses to your team. We accommodate different requirements and are flexible with seat count.
- +Bulk pricing available
- +Customizable content
- +Ready to start on your schedule
05 — Individual access
Simple, straightforward pricing.
Full platform access — every current and future course — priced so cost isn't what decides whether you learn.
No commitment required. Cancel anytime.