# AI Security Practitioner Training Course

> Source: https://lscs.io/ai-security-practitioner-course-details/
> Learn to secure LLM and agentic AI applications in this 3-day AI Security Practitioner course. Hands-on labs, BCS Tech10 accredited.

**We give you the frameworks, the foresight, and the authority to lead in AI security.**

- 3 Days Intensive Training
- Industry aligned

**Course Authored By:**

**Dhananjoy Chowdhury**

### PRICE:

### £1500

[ENTERPRISE TRAINING](https://lscs.io/enterprise-training-request-form/)

- Secure Payment via Stripe
- 7-Day Money-Back Guarantee

**Next Session Starts:**

[Contact us for dates](https://lscs.io/contact/)

**Application Deadline:**

[Contact us](https://lscs.io/contact/)

**Program Duration**

3 Days Intensive training

**Course' Mode Of Delivery**

Instructor Led (Onsite or Virtual)

**Hands-on Labs (Online)**

Apply what you learn with exercises and labs

[Contact Us](https://lscs.io/contact/)

**"An intensive hands-on programme that equips IT and cybersecurity professionals to understand AI technologies, identify AI-driven threats, secure LLM and agentic applications, and implement technical and risk controls. Participants gain practical lab experience, governance awareness, and the skills needed to protect organizations from emerging AI-powered cyber risks."**

## COURSE OVERVIEW

#### Stop feeling overwhelmed by the AI revolution. Become the proactive, trusted, and essential architect of your organization's AI defense.

An intensive hands-on programme that equips IT and cybersecurity professionals to understand AI technologies, identify AI-driven threats, secure LLM and agentic applications, and implement technical and risk controls. Participants gain practical lab experience, governance awareness, and the skills needed to protect organizations from emerging AI-powered cyber risks.

Join this 3-days course to explore AI and cybersecurity’s relationship. This course covers AI implementations, threats, attacks, and necessary controls for secure systems.

Gain insights into AI’s complexities in cybersecurity, learn real-life industry use cases, and discover techniques to protect your organization against emerging AI-powered threats.

### Career Value Add

- Foundational Knowledge: Gain an understanding of both AI technologies and cybersecurity fundamentals
- Insight into AI Threats: Learn about the vulnerabilities associated with AI systems, how they are exploited.
- Defensive Strategies: Acquire practical skills in protecting AI systems.
- Strategic Insight: Equip yourself with the knowledge to think strategically about AI security in a business context.
- Professional Growth: Earn a certificate upon completion, validating your expertise in AI Security Fundamentals.

### What You Will Learn

- Overview of Artificial Intelligence including Agentic AI
- Practical applications of AI
- AI in Cybersecurity
- AI as a threat
- AI Frameworks
- Leveraging AI for continuous monitoring
- Encryption, Data Protection and AI
- AI Risk and Compliance Management
- Roles and Responsibilities for AI and cybersecurity

### Business Takeaways

- Overview of Artificial Intelligence
- Practical Use cases of AI
- AI as a threat and a control
- Simulate AI driven attacks
- Securing AI systems
- Leveraging AI for technical controls
- Managing cybersecurity risks related to AI systems
- Assessing cybersecurity risks of AI systems
- Governing use of AI systems

### What You Will Get

- 30+ Video Lessons
- Completion Certificate from London School Of Cybersecurity
- Digital Certification Badge from The British Computer School (BCS, The Chartered Institute for IT)
- 30 Days Access To Hands-on Labs
- Digital & Physical Materials

## Course Curriculum

**Day 1**

**Introduction to the ‘AI Explosion’**

- Overview of Artificial Intelligence
- What is AI?
- History and Evolution of AI
- Types of AI
- Agentic AI and AI Agents
- Overview of Model Context Protocol (MCP) Overview
- Applications of AI in Different Industries
- AI in Cybersecurity
- Threat Detection: AI systems identifying anomalies and potential breaches
- Incident Response: Automated systems responding to cyber threats
- Predictive Analysis: Using AI to forecast potential security incidents
- AI as a Threat
- AI-Powered Attacks: Hackers leveraging AI to create sophisticated attacks
- Adversarial AI: Manipulating AI systems to alter data and make wrong decisions
- Deepfakes and Phishing: AI-generated content used for deceptive practices
- Hands-On Lab
- Create a AI Generated phishing campaign
- Create AI powered attack

**Day 2**

**Technical Mitigation Controls**

- Threats to AI Systems
- Robust AI Frameworks
- Implementing secure AI development practices
- Regular audits and updates to AI models
- OWASP Top 10 for LLM Applications
- OWASP Top 10 for Agentic Applications 2026
- Agentic AI and MCP Security Controls
- LLM Application Security
- Input/output validation and sanitization
- Implementing guardrails and safety filters
- Rate limiting and token management
- Output filtering and content moderation
- Advanced Threat Detection Systems
- Leveraging AI for continuous monitoring
- Incorporating anomaly detection algorithms
- Encryption and Data Protection
- Ensuring data integrity and confidentiality
- Using AI for enhanced encryption techniques
- Use Case Deep Dive and Hands On Lab
- Testing AI security
- Simulating attacks on AI systems
  - Prompt injection demonstration
  - Deepfake detection exercise
- Implementing defenses
  - Secure MCP server deployment

**Day 3**

**Risk Management Controls**

- AI Risk Management
- Developing a comprehensive AI risk management strategy
- Policies and Standards
- Training staff on AI Adoption
- Risks and secure adoption
- AI Governance Frameworks
- Risk Assessment
- Identifying potential AI-related risks
- Risk and Control Self-Assessments Use Cases
- Third-Party AI Risk Management
- AI Vendor Due Diligence
- Compliance and Regulatory Considerations
- Available industry standards and regulations
- Implementing AI-specific organization policies
- Roles & Responsibilities
- Evolving roles and responsibilities in managing AI risks
- Potential new roles to manage AI adoption and risks
- Use Case Deep-dive
- Conduct sample risk assessment
- AI incident response tabletop exercise
- Using AI to create engaging Security Awareness materials

**Key Takeways**

- Understand core AI concepts, types, and real-world applications across industries.
- Learn how AI supports cybersecurity operations such as detection and response.
- Recognise AI-powered threats including deepfakes, automated phishing, and adversarial manipulation.
- Experience simulated AI-driven attack scenarios to build practical awareness.
- Apply security controls for AI and LLM applications such as input/output validation and guardrails.
- Implement monitoring, anomaly detection, and rate/token management techniques.
- Understand encryption and data protection considerations in AI environments.
- Gain hands-on experience testing vulnerabilities and implementing defensive measures.
- Develop a structured AI risk management and governance approach.
- Conduct AI risk and control assessments, including third-party and vendor due diligence.
- Align AI initiatives with policies, standards, and regulatory expectations.
- Define roles and responsibilities for secure and responsible AI adoption.

## Meet Your Authors

### Dhananjoy Chowdhury

**Founder of Sinevis, Course Author And Lead Trainer**

Seasoned cybersecurity leader and Principal Trainer at the London School of Cyber Security. With over 20 years of global experience across public and private sectors, specialising in advanced security solutions, automation, and risk management. A certified expert, STEM Ambassador, and Founder of Sinevis.

### Priyanka Chatterjee

**CEO, London School of Cyber Security And Principal Trainer**

Founding partner, Women in Cyber Security Middle East. With 20+ years of global experience. Leads initiatives to close the cybersecurity talent gap, mentors professionals worldwide, and an award-winning cybersecurity educator and community leader.

[Book A Seat Now](https://outlook.office.com/book/speaktoLSCS@lscs.io/)

## Related Courses And Pricing

| Course Name | Course Price | Next Session Date |
| --- | --- | --- |
| [Cyberforce](https://lscs.io/cyberforce-course-details/) | £1900 (Prices exclude applicable taxes) | [Contact us](https://lscs.io/contact/) |
| [Board Governance of Cybersecurity](https://lscs.io/board-governance-of-cybersecurity-course-details/) | £1900 (Prices exclude applicable taxes) | [Contact us](https://lscs.io/contact/) |
| [GRC Mentorship](https://lscs.io/grc-mentorship-course-details/) | £150/month (Prices exclude applicable taxes) | [Contact us](https://lscs.io/contact/) |

## What You Should Know About The Course

### Who is this course for?

- IT / Cybersecurity Professionals

### What are the course' pre-requisites?

- Computer (Laptop/Desktop) with Internet Access
- Participants are expected to have knowledge of systems and cybersecurity in an organization.

### Do I need prior AI knowledge?

Basic cybersecurity understanding is helpful but not mandatory.

### What does Day 1 focus on?

AI foundations, real-world use cases, and AI-driven threat awareness such as deepfakes and automated phishing.

### What happens on Day 2?

Technical mitigation controls, LLM guardrails, monitoring, anomaly detection, and vulnerability testing.

### What is covered on Day 3?

AI risk management, governance, compliance alignment, and defining secure AI roles and responsibilities.

### What skills will I gain?

Ability to secure AI systems, assess AI risks, and implement governance and compliance measures.

- [Frequently asked questions about the AI Security Practitioner course](https://www.prnewswire.com/news-releases/usd-189-70-bn-growth-in-cyber-security-market%E2%80%93driven-by-the-increasing-use-of-mobile-devices%E2%80%93technavio-301501676.html)