Safe and Secure Use of Large Language Models (LLMs)

“The NTUiTiV Difference” – This is Why This Course is Right for You

• Special Discounted Price of US$3,950 – the usual price is US$4,950
• Satisfaction Guaranteed – or we will give you your money back!
• 15% Early-bird Discount – for the first 3 people to register for any course
• 20% Group Discount – if you come with one or more colleagues
• No More Than 12 Delegates on the course – guaranteed

See our homepage for more detailed information about these NTUiTiV Differences.

Harness AI responsibly—build trust and prevent misuse with expert safeguards.

This comprehensive 5-day programme equips technical, data, and compliance professionals with the skills needed to deploy large language models securely. You’ll explore risk assessment frameworks, secure prompt design, misuse detection, privacy considerations, and governance. Through real-world case studies, hands-on workshops, and policy development exercises, you’ll graduate with actionable strategies to safeguard LLM deployment in your organisation.

 Why this course is important

• AI is powerful, but risky: Misuse of LLMs can lead to privacy breaches, bias, and reputational damage—organizations must implement strong safeguard strategies.

• Regulatory scrutiny is growing: As AI regulations evolve, professionals must ensure deployments comply with emerging data protection, ethical, and security standards.

• Trust equals adoption: Secure, trustworthy AI encourages adoption across teams, enabling organizations to reap benefits responsibly and sustainably.

 Who should attend

• Data scientists, machine learning engineers, and AI developers deploying or scaling LLMs

• Compliance, privacy, and cybersecurity professionals overseeing AI governance and risk management

• AI ethics officers, product owners, and tech leads integrating LLMs into enterprise workflows

• IT architects and DevOps teams managing secure models, prompt pipelines, and prompt monitoring infrastructures

 What you will learn

Over five intensive days, you will:

1. Assess and mitigate LLM risks – Identify misuse scenarios, adversarial prompts, and model vulnerabilities

2. Design secure prompts – Develop prompt architecture that minimizes leak risks and ensures safe model responses

3. Detect and prevent misuse – Build guardrails to catch harmful content, bias, and privacy violations

4. Embed privacy-by-design – Apply redaction, PII identification, and encryption in LLM input/output flows

5. Govern LLM rollout – Establish AI policies, approval workflows, and ethical use frameworks

6. Ensure AI explainability – Implement transparency techniques to trace model decisions

7. Prepare for regulation – Align practices with emerging AI safety standards and regulatory expectations

8. Deploy secure monitoring infrastructure – Set up logging, anomaly detection, and alerting systems

9. Develop and present an AI security roadmap – Create tailored strategies for safe LLM adoption in your context