Conversational AI & LLM Safety (Compliance Focus)

Develop practical LLM safety course knowledge covering conversational AI compliance, governance, testing, privacy, security and responsible deployment.

79
August 2026
  • Trust badge
  • Trust badge

Get this this CPD‑Accredited programme now. Be secure with a SSL-secured payment backed up by a 14‑day money‑back guarantee.

Overview

Are unsafe AI habits secretly exposing your business? 78% of top organisations deploy AI. However, reported AI incidents surged by 56%.

This course turns complex security into simple actions. You will master prompt injection and data leakage. Plus, eliminate dangerous hallucinations and bias very easily.

We even make compliance oversight completely stress-free. Protect your enterprise with practical AI safety today!

Learning Outcomes

By completing this course, learners will be able to:

  • Identify common LLM security risks across conversational AI deployments.
  • Explain hallucination, bias, data leakage, and misuse controls.
  • Analyse prompt injection and jailbreak threats affecting AI security.
  • Apply LLM security best practices when reviewing deployment safeguards.
  • Assess LLM security testing evidence and red-team findings.
  • Recommend monitoring controls supporting responsible AI deployment.

Certification Information

Certification Information

After completion, learners receive the following certificate: Certificate of Completion from Spanish Compliance Institute

It records successful completion of this structured training programme. It can support professional development and internal training records.

The certificate does not provide professional licensing or accreditation. It also does not imply government or regulator approval.

Curriculum

1

Module 1: Conversational AI, LLM Risk, and Compliance Responsibility

1 Hour

  • 1.1 Conversational AI, Chatbots, Copilots, and LLM System Roles
  • 1.2 Organizational Risk Exposure in AI-Enabled Communication
  • 1.3 Safety, Trustworthiness, Accuracy, and Accountability Requirements
  • 1.4 Compliance Roles Across Legal, Privacy, Security, Product, HR, and Operations
2

Module 2: LLM Safety Risks and Control Challenges

1 Hour

  • 2.1 Hallucinations, Inaccurate Outputs, and Misleading AI Responses
  • 2.2 Bias, Discrimination, Disparate Impact, and Fairness Testing
  • 2.3 Prompt Injection, Jailbreaks, Data Leakage, and Misuse Risk
  • 2.4 Human Oversight, Escalation, Review, and Output Verification
3

Module 3: USA Legal, Regulatory, and Enforcement Landscape

1 Hour

  • 3.1 FTC, Consumer Protection, AI Claims, and Deceptive Practices
  • 3.2 Privacy, Confidentiality, COPPA, HIPAA, GLBA, FERPA, and State Privacy Rules
  • 3.3 Employment AI, Civil Rights, ADA, EEOC Guidance, and Bias Audit Duties
  • 3.4 Financial, Healthcare, Education, and Public-Sector Compliance Expectations
4

Module 4: AI Governance, Policies, and Compliance Program Design

1 Hour

  • 4.1 AI Use-Case Inventory, Risk Classification, and Approval Workflow
  • 4.2 Vendor Due Diligence, Contract Controls, and Third-Party AI Assurance
  • 4.3 AI Acceptable Use Policy, Employee Controls, and Training Requirements
  • 4.4 Documentation, Audit Trails, Monitoring, Incident Response, and Corrective Action
5

Module 5: Technical Safeguards and Operational Assurance

1 Hour

  • 5.1 Red Teaming, Safety Testing, Model Evaluation, and Bias Assessment
  • 5.2 Guardrails, Retrieval Controls, Content Filters, and Secure AI Agent Design
  • 5.3 Access Controls, Data Minimization, Logging, Retention, and Cybersecurity Controls
  • 5.4 Continuous Monitoring, Compliance Evidence, Performance Review, and Responsible Deployment
6

Mock Exam

30 Minutes

  • This practice assessment reviews concepts, scenarios, terminology, and responsibilities. It prepares learners for the final course assessment.
7

Final Exam

30 Minutes

  • The final exam checks understanding across the complete course. Passing supports the certificate completion pathway.

Requirements

  • No coding experience is required for this course.
  • Basic compliance or technology familiarity can support learning.
  • Learners need a suitable internet-connected computer or mobile device.
  • Reliable internet access supports uninterrupted online learning.
  • An interest in AI safety supports course engagement.
  • Professional AI experience is helpful but not mandatory.

This Course Includes

  • Approximately six hours of self-paced online learning
  • Practical AI safety and security guidance
  • Governance and compliance-focused learning
  • LLM security testing concepts
  • Mock & final exam preparation
  • Certificate of completion

Why Choose Us

Spanish Compliance Institute connects professional learning with practical compliance realities. Lessons prioritise clear decisions, documented controls, and workplace application.

Flexible online study supports busy professionals and organisational teams. Completion also provides a clear record of structured learning.

Learners choose Spanish Compliance Institute because training is:

  • Clear, structured, and easy to follow
  • Designed around practical AI and LLM risks
  • Relevant to compliance and governance responsibilities
  • Suitable for busy professionals and organisational teams
  • Focused on workplace application
  • Completed with an institute certificate

Career Opportunities

This course can support professionals pursuing related responsibilities.

  • AI Governance Analyst
  • Responsible AI Specialist
  • AI Risk Analyst
  • AI Compliance Analyst
  • Technology Risk Consultant
  • Privacy and AI Governance Specialist

The course strengthens knowledge relevant to these emerging responsibilities. It does not guarantee employment, promotion, or professional status.

More About This Course

Building Practical AI and LLM Safety Foundations

AI & LLM safety training connects governance with everyday deployment. Learners study system roles, accuracy, trustworthiness, and accountability.

The course explains where AI safety and security intersect. It separates technical controls from organisational compliance responsibilities.

Understanding LLM Security Risks and Misuse

LLM security risks extend beyond inaccurate or biased outputs. They include prompt injection, jailbreaks, leakage, and unsafe automation.

OWASP identifies prompt injection among major LLM application risks. The course connects those threats with practical control decisions.

Testing, Benchmarks, and Operational Assurance

LLM security testing helps teams identify weaknesses before deployment. Red teaming examines misuse, bias, manipulation, and guardrail failures.

An LLM safety benchmark can support repeatable evaluation criteria. LLM safety tools should complement documented human review processes.

Building an Effective LLM Safety Framework

An LLM safety framework organises policies, controls, and monitoring. It creates clearer ownership across security, legal, and product teams.

NIST provides voluntary guidance for generative AI risk management. See NIST's Generative AI Profile for external guidance.

Governance, Compliance, and Human Oversight

AI security alone cannot manage every compliance concern. Governance assigns decision rights, documentation duties, and escalation routes.

International teams may also face European AI requirements. Explore EU AI Act and AI Governance for Business for European context.

Supporting Responsible AI Careers and Organisational Capability

Growing AI careers increasingly combine technology knowledge with governance awareness. This course supports professionals navigating AI security responsibilities.

Practical learning helps teams keep AI safer during deployment. It also strengthens evidence, review, and incident-response discipline.

Frequently Asked Questions

AI and LLM safety reduces harmful, unreliable, or insecure outcomes. It combines governance, testing, safeguards, and human oversight.

Major LLM security risks include hallucinations, bias, leakage, and manipulation. Prompt injection and unsafe automation create additional exposure.

Verify important claims against trusted, authoritative, and current sources. Escalate high-impact outputs before decisions or external communication.

Developers use testing, guardrails, access controls, and monitoring. LLM security testing should include adversarial and misuse scenarios.

No. Safety controls reduce risk but cannot remove everything. Continuous evaluation and human review remain important.

People provide context, judgement, escalation, and organisational accountability. Oversight becomes crucial when AI affects rights or safety.

Yes, the course includes a Spanish Compliance Institute completion certificate. It is not government accreditation or professional licensing.

No coding experience is required. Basic compliance, security, or technology familiarity can help.

Share This Course