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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.
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
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
Knowledge Check: Introduction to AI•30 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
Generative AI Security Fundamentals
Module 2•2 hours to complete
Module details
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.
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
Practice Quiz: Introduction to Prompt Engineering•6 minutes
Practice Quiz: Hands-On with LLMs for Cybersecurity Applications•6 minutes
Knowledge Check: Generative AI Security Fundamentals•30 minutes
2 discussion prompts•Total 10 minutes
Prompt-Based Systems Pitfalls•5 minutes
Leveraging LLMs for Cybersecurity•5 minutes
Security in AI System Architectures
Module 3•2 hours to complete
Module details
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.
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
Practice Quiz: AI System Components and Security Considerations•6 minutes
Practice Quiz: Introduction to Adversarial Machine Learning•6 minutes
Knowledge Check: Security in AI System Architectures•30 minutes
2 discussion prompts•Total 10 minutes
Prioritizing AI Security Measures•5 minutes
Adversarial Machine Learning Risks•5 minutes
Course Wrap-Up and Assessment
Module 4•2 hours to complete
Module details
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
Show info about module content
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
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highest course completion rate in the industry and we strive to create an online ecosystem for our global learners to equip
themselves with industry-relevant skills in today’s cutting edge technologies.
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.
What topics are covered in this course?
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.
Will I get hands-on practice with AI tools?
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.
What skills will I gain from this course?
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.
How long will it take to complete the course?
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.
Do I need programming or AI expertise to enroll?
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.
Will I receive a certificate upon completion?
Yes, after successfully finishing all modules and graded assessments, you will receive a certificate of completion to validate your understanding of AI in cybersecurity.
How is this course different from other AI or cybersecurity programs?
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.
When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
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.