As AI becomes a bigger part of our apps and systems, it’s also becoming a new target for cyber threats. This course, Building Security into AI is all about helping you understand where those risks come from and what you can actually do about them. Taught by Robert Herbig an experienced AI practitioner and security focused software leader. The course takes you through real-world examples simple threat models and practical advice to make your AI systems safer. It’s not about overwhelming you with buzzwords or frameworks you won’t need to be a cybersecurity expert or an AI researcher to keep up. If you’re a developer, engineer or just someone working with AI-powered software this course gives you a solid foundation to spot the risks and build smarter, more secure AI features.
My Thoughts
I was really intrigued by this course, and it didn’t disappoint. I am not an AI expert but this course opened my eyes to the many security challenges that come with building AI-enabled applications. I learned a lot from how AI systems are structured to the real world risks they face and how attackers exploit them. The examples were practical and the way the material was presented made complex ideas easy to understand. It definitely gave me a new perspective on both AI and cybersecurity.
Who Should Take This Course?
- Software engineers and developers
- Security professionals (InfoSec, AppSec, DevSecOps)
- AI/ML practitioners and data scientists
- Product managers and tech leads
- QA engineers and testers
- System architects
- Students and learners in cybersecurity or AI
- Business stakeholders and non-technical leaders
- Compliance and risk management teams
- Everyody that like knowledge 🙂
Course Curriculum
- Introduction
- How are AI applications structured
- Internal Data
- External Dependencies
- Model Training Process
- Input Manipulation
- Input-based Attacks
- Prompt Injection
- Indirect Attacks
- Data Output Concerns
Thats all!
Keep Hacking!
//Roger
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