What you'll learn:
- Understand how ChatGPT, GPT-5, Claude and other LLMs work from a security and risk management perspective.
- Identify common AI security threats including prompt injection, data leakage, model abuse and adversarial attacks.
- Apply AI security frameworks such as NIST AI RMF and other governance standards to real-world situations.
- Protect sensitive business, customer and organizational data when using AI-powered tools and platforms.
- Evaluate privacy risks associated with AI systems, file uploads, memory features and third-party integrations.
- Build threat models for Generative AI systems and identify vulnerabilities before deployment.
- Secure AI applications, APIs and deployment environments using practical security best practices.
- Understand AI compliance, ethics, governance and responsible AI principles in modern organizations.
- Reduce hallucinations and improve AI output quality through verification and quality control processes.
- Develop AI risk management strategies that balance innovation, privacy, security and business goals.
WHAT STUDENTS ARE SAYING (REAL RESULTS, REAL PEOPLE)
"This course opened my eyes to AI security risks I never knew existed. Essential knowledge for anyone working with ChatGPT or LLMs in their organization." — Michael Chen (5 stars)
"Finally, a course that explains AI security without the technical jargon. Practical, actionable, and immediately applicable to my work." — Sarah Williams (5 stars)
"The instructor breaks down complex security concepts into digestible lessons. I now understand how to protect my company's data when using AI tools." — David Martinez (5 stars)
"Comprehensive coverage of AI security from data privacy to model protection. This should be mandatory for every business using generative AI." — Jennifer Park (5 stars)
AI Security & Privacy: ChatGPT, Claude, GPT-5 & LLMs
Artificial Intelligence is no longer a futuristic concept.
Today, businesses, governments, startups, consultants, educators, marketers, developers, financial professionals, healthcare providers, and students are using AI-powered tools such as ChatGPT, Claude, GPT-5, Gemini, Copilot, and other Large Language Models (LLMs) to improve productivity, automate tasks, analyze information, generate content, and make better decisions.
However, as AI adoption accelerates across industries, a critical challenge has emerged:
Most people understand how to use AI.
Very few understand how to use AI securely.
Organizations are uploading confidential business information into AI systems. Employees are sharing sensitive customer data with AI assistants. Teams are making important decisions based on AI-generated outputs without understanding their limitations. Businesses are deploying AI applications without proper security controls, governance frameworks, privacy protections, or risk management processes.
The result?
Data leaks.
Privacy violations.
Compliance failures.
Intellectual property exposure.
Model abuse.
Security incidents.
And growing business risk.
This course was created to help solve that problem.
Whether you are a business professional, entrepreneur, consultant, manager, student, developer, analyst, cybersecurity practitioner, compliance officer, or simply someone who wants to use AI responsibly, this course will help you understand the security, privacy, governance, and risk considerations surrounding modern AI systems.
Unlike traditional cybersecurity courses that focus primarily on networks, operating systems, and infrastructure, this course focuses specifically on the new challenges introduced by Generative AI and Large Language Models.
You will learn not only how these systems work but also where vulnerabilities exist, how attackers exploit weaknesses, and what practical steps organizations can take to protect themselves.
The course is designed for beginners while still providing valuable insights for experienced professionals seeking to understand AI-specific security risks.
We begin by building a strong foundation.
You will first learn how Generative AI works, why AI security matters, and how the rapid adoption of tools such as ChatGPT and Claude is creating new opportunities and risks for organizations around the world.
You will explore:
• What Generative AI is and how it differs from traditional software
• Why AI security is becoming one of the most important skills of the decade
• Common threats facing AI systems today
• Real-world AI security incidents and lessons learned
• Emerging risks associated with intelligent AI systems and future developments
• The impact of AI on business, careers, and organizational risk management
Next, we dive deep into Large Language Models.
Many professionals use LLMs every day but have little understanding of how they actually function.
This section helps bridge that gap.
You will learn:
• How Large Language Models are trained
• How LLMs generate responses
• How attackers view AI systems
• Neural networks, embeddings, and transformer architectures explained in simple language
• Why hallucinations occur
• Why AI systems sometimes generate inaccurate information
• Reliability challenges in AI outputs
• Verification strategies for AI-generated content
• Understanding AI trustworthiness and confidence levels
Once you understand the technology, we move into governance, compliance, and responsible AI practices.
As governments and regulators increase scrutiny of AI systems, organizations must balance innovation with accountability.
In this section, you will explore:
• AI governance fundamentals
• Responsible AI principles
• Ethical AI development and deployment
• AI bias and fairness considerations
• Privacy obligations and responsibilities
• Data governance best practices
• Regulatory compliance requirements
• The NIST AI Risk Management Framework
• ISO-related AI security concepts
• Practical approaches to building trust in AI systems
The course then introduces one of the most important disciplines in modern AI security:
Threat Modeling.
Threat modeling allows organizations to identify risks before they become incidents.
You will learn:
• AI threat modeling fundamentals
• AI attack surfaces
• Prompt injection attacks
• Adversarial manipulation techniques
• Data poisoning concepts
• Model exploitation strategies
• Threat modeling frameworks
• Privacy-focused threat analysis
• Security assessment methodologies
• Practical exercises for evaluating AI system risks
After understanding threats, we focus on protecting one of the most valuable assets in any AI system:
Data.
Data is the fuel that powers modern AI.
Unfortunately, it is also one of the most common sources of security and privacy failures.
You will learn:
• AI data security fundamentals
• Data confidentiality risks
• Data leakage scenarios
• Unauthorized access threats
• Sensitive information exposure
• Secure data handling practices
• Encryption concepts
• Data minimization strategies
• Privacy-preserving approaches
• Best practices for protecting business and customer information
The course then explores model security and intellectual property protection.
As organizations invest significant resources into training and deploying AI systems, protecting those assets becomes increasingly important.
You will discover:
• Model theft risks
• Intellectual property protection strategies
• AI model security controls
• Watermarking techniques
• Digital rights management approaches
• Model protection best practices
• Risks associated with model replication
• Defensive strategies for safeguarding AI investments
We then move into deployment security.
Building an AI model is only part of the challenge.
Deploying it securely is equally important.
This section covers:
• Secure AI infrastructure design
• AI deployment security principles
• API security best practices
• Authentication and authorization controls
• Monitoring AI applications
• Logging and auditing strategies
• Intrusion detection concepts
• Incident response considerations
• Operational security for AI environments
One of the most practical and relevant sections of this course focuses on privacy risks associated with popular AI platforms.
Every day, professionals upload contracts, financial documents, business plans, customer records, marketing strategies, code repositories, and confidential information into AI tools.
Many do not fully understand the implications.
In this dedicated privacy section, you will learn:
• What information should never be uploaded to AI systems
• How ChatGPT handles user data
• Understanding ChatGPT memory features
• What AI systems may retain
• Data retention and privacy considerations
• Secure file upload practices
• Risks associated with sharing confidential information
• Protecting intellectual property when using AI
• Comparing privacy approaches across major AI platforms
• ChatGPT versus Claude privacy considerations
• Best practices for professionals working with sensitive information
You will also explore:
• AI-assisted work and ethical responsibilities
• Avoiding plagiarism and intellectual property issues
• Safe use of AI in professional environments
• Advertising and marketing risks associated with AI-generated content
• Organizational AI usage policies
• Quality control frameworks for AI-generated outputs
• Human oversight requirements
• Building responsible AI workflows
Throughout the course, you will encounter real-world examples, practical frameworks, security concepts, governance models, privacy discussions, and actionable recommendations that can be applied immediately in your career or organization.
By the end of this course, you will be able to:
• Understand how modern AI systems work from a security perspective
• Identify common AI vulnerabilities and risks
• Evaluate privacy implications when using AI tools
• Protect sensitive information in AI environments
• Apply AI governance and compliance principles
• Build threat models for Generative AI systems
• Secure AI deployments and APIs
• Improve AI output reliability and trustworthiness
• Reduce organizational risk associated with AI adoption
• Make better decisions when implementing AI technologies
Artificial Intelligence will continue transforming the way we work, communicate, create, and make decisions.
The professionals who thrive in this new era will not simply be those who know how to use AI.
They will be the ones who understand how to use it securely, responsibly, ethically, and effectively.
If you want to become one of those professionals, this course is for you.
Enroll today and build the knowledge, awareness, and practical skills needed to navigate the rapidly evolving world of AI security, privacy, governance, and risk management.
