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Generative AI for Security Fundamentals

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Generative AI for Security Fundamentals

This course is part of AI Security Specialization

Instructor: Edureka

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

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.

Details to know

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Assessments

12 assignments¹

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the AI Security Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • 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 videosTotal 95 minutes
  • Specialization Introduction7 minutes
  • Course Introduction5 minutes
  • The Role of AI in Cybersecurity6 minutes
  • Traditional Security vs. AI Security7 minutes
  • Real-world Applications of AI in Cyber Defense7 minutes
  • What is Generative AI?7 minutes
  • Core Generative AI Modeling Concepts6 minutes
  • Key Models in Generative AI (GANs, VAEs, LLMs)6 minutes
  • Transformers: The AI Backbone7 minutes
  • Demonstration: Visualizing Attention in Transformer Model7 minutes
  • Applications of GenAI in Cybersecurity6 minutes
  • What Are Large Language Models?5 minutes
  • Key LLM Models (GPT, Gemini, LLaMA)6 minutes
  • LLM Capabilities and Limitations in Cybersecurity7 minutes
  • Demonstration: Designing Creative Prompts for LLM Tasks6 minutes
7 readingsTotal 80 minutes
  • Course Overview15 minutes
  • AI for Malware Detection10 minutes
  • Introduction to Generative AI Tools10 minutes
  • Overview of BERT, GPT, and Hugging Face10 minutes
  • Usecases of LLMs in Various Domains10 minutes
  • Deep Learning Architectures for Security10 minutes
  • Module Summary: Introduction to AI15 minutes
4 assignmentsTotal 48 minutes
  • Knowledge Check: Introduction to AI30 minutes
  • Practice Quiz: Overview of AI in Cybersecurity6 minutes
  • Practice Quiz: Introduction to Generative AI6 minutes
  • Practice Quiz: Understanding Large Language Models (LLMs)6 minutes
4 discussion promptsTotal 20 minutes
  • Introduce Yourself5 minutes
  • AI Cybersecurity Challenges5 minutes
  • GenAI’s Impact on Cybersecurity5 minutes
  • LLM Security Risks in Enterprises5 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 videosTotal 55 minutes
  • Basics of Prompt Engineering7 minutes
  • Techniques for Crafting Secure Prompts5 minutes
  • Risks Associated with Improper Prompting6 minutes
  • Demonstration: Crafting Zero Shot, One Shot and Few Shot prompts7 minutes
  • Advanced Prompt Techniques5 minutes
  • Demonstration: Effective Prompt Design Strategies7 minutes
  • Demonstration: LLMs for Threat Detection and Analysis6 minutes
  • GenAI for Security Automation and Intelligence5 minutes
  • Demonstration: Evaluating LLM Output for Security Risks7 minutes
3 readingsTotal 35 minutes
  • Prompt Injection and Manipulation10 minutes
  • AI for Identity Management10 minutes
  • Module Summary: Generative AI Security Fundamentals15 minutes
3 assignmentsTotal 42 minutes
  • Knowledge Check: Generative AI Security Fundamentals30 minutes
  • Practice Quiz: Introduction to Prompt Engineering6 minutes
  • Practice Quiz: Hands-On with LLMs for Cybersecurity Applications6 minutes
2 discussion promptsTotal 10 minutes
  • Prompt-Based Systems Pitfalls5 minutes
  • Leveraging LLMs for Cybersecurity5 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 videosTotal 41 minutes
  • The Architecture of AI Systems6 minutes
  • Identifying Vulnerabilities in AI Components6 minutes
  • Security Best Practices for AI Systems5 minutes
  • What is Adversarial Machine Learning?7 minutes
  • Methods of Crafting Adversarial Attacks6 minutes
  • Defending AI Systems Against Adversarial Threats5 minutes
  • Demonstration: Shielding AI from Adversarial Threats6 minutes
3 readingsTotal 35 minutes
  • Basic Network Security for AI Models10 minutes
  • DDoS Detection with AI10 minutes
  • Module Summary: Security in AI System Architectures15 minutes
3 assignmentsTotal 42 minutes
  • Knowledge Check: Security in AI System Architectures30 minutes
  • Practice Quiz: AI System Components and Security Considerations6 minutes
  • Practice Quiz: Introduction to Adversarial Machine Learning6 minutes
2 discussion promptsTotal 10 minutes
  • Prioritizing AI Security Measures5 minutes
  • Adversarial Machine Learning Risks5 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 videoTotal 3 minutes
  • Course Summary3 minutes
1 readingTotal 30 minutes
  • Practice Project: Securing AI-Driven Cybersecurity Tasks with Generative AI30 minutes
2 assignmentsTotal 60 minutes
  • Implementing AI-Driven Cybersecurity Operations30 minutes
  • End Course Knowledge Check: Generative AI for Security Fundamentals30 minutes
1 discussion promptTotal 5 minutes
  • Describe Your Learning Journey5 minutes

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Instructor

Edureka
203 Courses185,724 learners

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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.

By completing the course, you will be able to:

Distinguish between traditional AI, LLMs, and Generative AI in a security context.

Apply secure prompt engineering techniques and identify prompt injection risks.

Use LLMs to automate threat detection and security intelligence tasks.

Recognize vulnerabilities in AI architectures and defend against adversarial attacks.

Integrate AI-driven security measures into enterprise cybersecurity strategies.

The course is designed to be completed in 3-4 weeks, with a recommended study pace of 4–5 hours per week. You can progress at your own pace, revisiting readings, videos, and quizzes as needed.

No. This course does not require prior programming or AI experience. All key concepts, tools, and techniques are explained step-by-step with a focus on cybersecurity applications.

Yes, after successfully finishing all modules and graded assessments, you will receive a certificate of completion to validate your understanding of AI in cybersecurity.

Unlike generic AI or security courses, this program focuses on practical cybersecurity applications of AI and Generative AI. It blends real-world demos, hands-on labs, and case studies to help you bridge the gap between AI technology and cyber defense strategies.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.