If you are looking for AI security training, I would focus less on the course title and more on what you actually get to practice. AI security covers areas such as LLM applications, prompt injection, RAG, AI agents, MCP, data exposure, model security, threat modeling, and defensive controls. A course that only explains these topics at a high level may not be enough for someone who wants to apply them in security work.

One course worth considering is the Certified AI Security Expert (MSec-CAIS) from Modern Security. The course is designed around hands-on AI and LLM security training and is suitable for security engineers, developers, *********** testers, red teamers, and technical leaders. It also starts with AI and LLM fundamentals, so prior AI knowledge is not required.

What Does the Course Cover?

The training follows a practical build, break, and defend approach.

It first covers how modern AI applications are built, including LLM APIs, embeddings, vector databases, RAG, agentic systems, MCP, and related tools. Students also build a threat model agent as part of the practical work.

The offensive section then looks at real attack scenarios. These include prompt injection, indirect prompt injection, sensitive information disclosure, authorization problems, MCP attacks, agent security issues, and model backdoors.

The defensive side focuses on techniques such as LLM guardrails, MCP gateways, application-level fixes, and security architecture for AI agents. The stated goal is to help learners understand how production AI applications are built, assess their risks, and provide practical security recommendations.

Is It Suitable for Beginners?

The course does not require an AI background. Its curriculum starts with AI, machine learning, generative AI, and LLM foundations before moving into application development and security testing.

That makes it useful for security professionals who understand cybersecurity but want to build a stronger foundation in how AI applications work before testing them.

How Practical Is the Training?

Hands-on work is one of the main parts of the course. The curriculum includes building an LLM application, creating an internal security chatbot using RAG, working with AI agents and function calls, building a web security scanner agent, testing prompt injection, examining sensitive information disclosure, working with AI supply chain security, and testing MCP security.
The course also covers defensive testing with tools such as Garak, along with techniques for handling prompt injection and sensitive information disclosure.

Who Should Consider It?

This type of AI security certification can be useful for:

Security engineers working with AI applications
Developers building LLM-based applications
*********** testers and red teamers
Application security professionals
Technical leaders who need to understand AI security risks

The course is self-paced and includes video lessons and hands-on labs. It also provides a certificate of completion.

The instructor, Harish Ramadoss, has a background in product security, red teaming, and security research, and the course page notes his previous work at Trustwave SpiderLabs and Rippling, along with security conference presentations.

For someone comparing AI security courses, the main thing I would check is whether the training gives you enough practical work to understand how AI systems are built, how they can be attacked, and how those weaknesses can be addressed. Based on the published curriculum, the Certified AI Security Expert course is a strong option for people who want that combination rather than a course focused only on AI security theory.

Course Link: https://www.modernsecurity.io/courses/ai-security-certification

Website: https://www.modernsecurity.io/