Generative AI for Security Fundamentals
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Generative AI for Security Fundamentals
This course is part of AI Security Specialization
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What you'll learn
Describe core concepts of AI, Generative AI, and LLMs within modern cybersecurity.
Explain security implications and key risks of using Generative AI and LLMs in enterprises.
Apply prompt engineering and secure techniques to reduce prompt injection and adversarial threats.
Evaluate AI architectures and enforce best practices to protect models, data pipelines, and defenses.
Skills you'll gain
- Distributed Denial-Of-Service (DDoS) Attacks
- Cyber Attacks
- Security Strategy
- Vulnerability Assessments
- Security Awareness
- Cyber Security Strategy
- Generative Model Architectures
- Prompt Patterns
- Threat Detection
- Information Systems Security
- Large Language Modeling
- Responsible AI
- Security Management
- Threat Modeling
- IT Security Architecture
- Enterprise Security
- Cloud Security
- Cybersecurity
- Cyber Threat Intelligence
- AI Security
Details to know
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- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this course
This program equips cybersecurity professionals, IT teams, and business leaders with foundational knowledge and practical skills to secure AI-driven systems using Generative AI and Large Language Models (LLMs). You’ll start by understanding AI’s role in cybersecurity, exploring traditional security methods, LLM architectures, and how GenAI applications are transforming threat detection and defense mechanisms.
Next, you’ll dive into Generative AI security fundamentals, learning prompt engineering techniques, risks of manipulation, and how to securely design interactions with AI models. You’ll also gain hands-on experience applying LLMs to threat analysis, identity management, and security automation. By the end of this program, you will be able to: - Explain the foundational concepts of AI and its implications for cybersecurity. - Differentiate between traditional AI, LLMs, and Generative AI applications in security contexts. - Apply secure prompt engineering methods and mitigate risks associated with AI interactions. - Use LLMs to enhance threat detection, identity management, and automation in security workflows. - Identify vulnerabilities in AI architectures and implement best practices to secure models - Understand adversarial machine learning techniques and deploy defenses to protect AI systems. - Evaluate AI-driven security processes for ethical, transparent, and resilient operations. This course is designed for cybersecurity engineers, AI security specialists, LLM engineers, ML engineers, and cloud/edge security architects looking to build expertise in AI security. Join us to develop the skills needed to protect modern cybersecurity environments with AI-powered solutions and best practices.
Discover how AI is transforming cybersecurity by improving threat detection, response, and defense strategies. Learn the fundamentals of AI, Generative AI, and Large Language Models (LLMs), and explore their applications in real-world cybersecurity scenarios. Apply insights from AI to enhance malware detection, secure interactions, and understand potential risks while building a strong foundation in AI-powered security practices.
What's included
15 videos7 readings4 assignments4 discussion prompts
15 videos•Total 95 minutes
- Specialization Introduction•7 minutes
- Course Introduction•5 minutes
- The Role of AI in Cybersecurity•6 minutes
- Traditional Security vs. AI Security•7 minutes
- Real-world Applications of AI in Cyber Defense•7 minutes
- What is Generative AI?•7 minutes
- Core Generative AI Modeling Concepts•6 minutes
- Key Models in Generative AI (GANs, VAEs, LLMs)•6 minutes
- Transformers: The AI Backbone•7 minutes
- Demonstration: Visualizing Attention in Transformer Model•7 minutes
- Applications of GenAI in Cybersecurity•6 minutes
- What Are Large Language Models?•5 minutes
- Key LLM Models (GPT, Gemini, LLaMA)•6 minutes
- LLM Capabilities and Limitations in Cybersecurity•7 minutes
- Demonstration: Designing Creative Prompts for LLM Tasks•6 minutes
7 readings•Total 80 minutes
- Course Overview•15 minutes
- AI for Malware Detection•10 minutes
- Introduction to Generative AI Tools•10 minutes
- Overview of BERT, GPT, and Hugging Face•10 minutes
- Usecases of LLMs in Various Domains•10 minutes
- Deep Learning Architectures for Security•10 minutes
- Module Summary: Introduction to AI•15 minutes
4 assignments•Total 48 minutes
- Knowledge Check: Introduction to AI•30 minutes
- Practice Quiz: Overview of AI in Cybersecurity•6 minutes
- Practice Quiz: Introduction to Generative AI•6 minutes
- Practice Quiz: Understanding Large Language Models (LLMs)•6 minutes
4 discussion prompts•Total 20 minutes
- Introduce Yourself•5 minutes
- AI Cybersecurity Challenges•5 minutes
- GenAI’s Impact on Cybersecurity•5 minutes
- LLM Security Risks in Enterprises•5 minutes
Learn how AI enhances cybersecurity by enabling secure interactions with Generative AI and LLMs. Explore prompt engineering techniques to mitigate risks, design safe AI workflows, and evaluate AI outputs for threats. Gain practical skills to apply AI in threat detection, security automation, and risk assessment while ensuring ethical and resilient AI usage.
What's included
9 videos3 readings3 assignments2 discussion prompts
9 videos•Total 55 minutes
- Basics of Prompt Engineering•7 minutes
- Techniques for Crafting Secure Prompts•5 minutes
- Risks Associated with Improper Prompting•6 minutes
- Demonstration: Crafting Zero Shot, One Shot and Few Shot prompts•7 minutes
- Advanced Prompt Techniques•5 minutes
- Demonstration: Effective Prompt Design Strategies•7 minutes
- Demonstration: LLMs for Threat Detection and Analysis•6 minutes
- GenAI for Security Automation and Intelligence•5 minutes
- Demonstration: Evaluating LLM Output for Security Risks•7 minutes
3 readings•Total 35 minutes
- Prompt Injection and Manipulation•10 minutes
- AI for Identity Management•10 minutes
- Module Summary: Generative AI Security Fundamentals•15 minutes
3 assignments•Total 42 minutes
- Knowledge Check: Generative AI Security Fundamentals•30 minutes
- Practice Quiz: Introduction to Prompt Engineering•6 minutes
- Practice Quiz: Hands-On with LLMs for Cybersecurity Applications•6 minutes
2 discussion prompts•Total 10 minutes
- Prompt-Based Systems Pitfalls•5 minutes
- Leveraging LLMs for Cybersecurity•5 minutes
Explore how AI system architectures can be secured to protect against cyber threats and adversarial attacks. Learn to identify vulnerabilities in AI components, implement best practices for system protection, and defend networks. Gain hands-on experience with adversarial attack simulations, vulnerability assessments, threat modeling, and AI security strategies to ensure resilient and robust AI-driven systems.
What's included
7 videos3 readings3 assignments2 discussion prompts
7 videos•Total 41 minutes
- The Architecture of AI Systems•6 minutes
- Identifying Vulnerabilities in AI Components•6 minutes
- Security Best Practices for AI Systems•5 minutes
- What is Adversarial Machine Learning?•7 minutes
- Methods of Crafting Adversarial Attacks•6 minutes
- Defending AI Systems Against Adversarial Threats•5 minutes
- Demonstration: Shielding AI from Adversarial Threats•6 minutes
3 readings•Total 35 minutes
- Basic Network Security for AI Models•10 minutes
- DDoS Detection with AI•10 minutes
- Module Summary: Security in AI System Architectures•15 minutes
3 assignments•Total 42 minutes
- Knowledge Check: Security in AI System Architectures•30 minutes
- Practice Quiz: AI System Components and Security Considerations•6 minutes
- Practice Quiz: Introduction to Adversarial Machine Learning•6 minutes
2 discussion prompts•Total 10 minutes
- Prioritizing AI Security Measures•5 minutes
- Adversarial Machine Learning Risks•5 minutes
This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz.
What's included
1 video1 reading2 assignments1 discussion prompt
1 video•Total 3 minutes
- Course Summary•3 minutes
1 reading•Total 30 minutes
- Practice Project: Securing AI-Driven Cybersecurity Tasks with Generative AI•30 minutes
2 assignments•Total 60 minutes
- Implementing AI-Driven Cybersecurity Operations•30 minutes
- End Course Knowledge Check: Generative AI for Security Fundamentals•30 minutes
1 discussion prompt•Total 5 minutes
- Describe Your Learning Journey•5 minutes
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Frequently asked questions
This course is ideal for cybersecurity professionals, IT security analysts, SOC (Security Operations Center) members, developers, and technology leaders who want to understand how AI and Generative AI impact cybersecurity. No prior experience with AI or data science is required, but basic cybersecurity concepts are helpful.
The course begins with the foundations of AI in cybersecurity, explaining the differences between traditional AI, Large Language Models (LLMs), and Generative AI. You will learn about prompt engineering, secure use of LLMs, and AI system architectures. Topics include:
Real-world applications of AI in malware detection and cyber defense
Generative AI security fundamentals and prompt-related risk mitigation
Adversarial machine learning and defending AI systems from attacks
Best practices for securing AI models and data pipelines.
Yes! The course includes interactive demos and practice exercises using real-world cybersecurity scenarios. You will work with LLMs for threat detection and analysis, practice prompt engineering (zero-shot, one-shot, few-shot), and experiment with adversarial attack simulations and defense strategies.
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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.
