Will I earn university credit for completing the Specialization?

No, this Specialization does not provide university credit. However, you will earn a Coursera certificate, which can be shared on LinkedIn or added to your CV to demonstrate industry-relevant skills.

What will I be able to do upon completing the Specialization?

You will be able to analyze vulnerabilities in generative AI models, apply defensive techniques to secure AI systems, and design safe, responsible AI workflows for real-world applications.

How does this Specialization help my career?

This program prepares you for roles such as AI engineer, ML security specialist, data scientist, or cybersecurity analyst, bridging the gap between AI innovation and secure deployment.

Can I apply these skills immediately in my job?

Yes, the projects are designed to mirror real-world challenges, so you can directly apply the skills in AI development, enterprise adoption, or security operations.

Is this Specialization suitable for beginners in AI?

Yes, while some prior exposure to AI concepts is recommended, the first course covers foundational material to help you get started with generative AI.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

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.

Can I take the course for free?

No, you cannot take this course for free. 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. If you cannot afford the fee, you can apply for financial aid.

AI Security Specialization

Build Secure AI Systems. Learn to secure AI models, mitigate risks, and apply safe AI practices across real-world systems.

Instructor: Edureka

Included with Coursera Plus

Learn more

3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

2 months at 5 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

2 months at 5 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

What you'll learn

Understand the foundations of generative AI and large language models
Identify risks, threats, and vulnerabilities in AI-powered systems
Apply defensive strategies to secure and deploy safe AI workflows
Design responsible, ethical, and trustworthy AI applications

Overview

This Specialization prepares learners to design, deploy, and secure generative AI systems with confidence and responsibility. As generative AI and large language models (LLMs) transform industries, securing these technologies is critical. Through three courses, you will build foundational knowledge of generative AI, learn to recognize and mitigate risks, and gain hands-on practice in applying defensive strategies to protect AI-powered systems.

You will be able to explain generative AI fundamentals, identify vulnerabilities in AI workflows, implement security measures to defend against adversarial attacks, and design responsible AI deployments aligned with best practices.

This program is ideal for students, developers, AI engineers, data scientists, and cybersecurity professionals, as well as business and IT leaders who need to ensure safe AI adoption.

Basic knowledge of Python and familiarity with AI or machine learning concepts are recommended. No prior cybersecurity expertise is required.

Courses Included:

Generative AI for Security Fundamentals – Understand core AI architectures and security basics.
Generative AI and LLM Security – Focus on securing LLMs, safe deployment, and responsible use.
Securing AI Systems – Learn about vulnerabilities, adversarial attacks, and defenses.

By the end of this Specialization, you will have the skills to build secure, ethical, and trustworthy generative AI applications for real-world impact.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from Edureka

Specialization - 3 course series

Generative AI for Security Fundamentals

Course 110 hoursView course

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

Cybersecurity, Large Language Modeling, Threat Detection, Security Engineering, Cyber Attacks, Incident Response, Security Management, Cyber Security Strategy, Security Strategy, Distributed Denial-Of-Service (DDoS) Attacks, IT Security Architecture, Enterprise Security, Artificial Intelligence, Data Ethics, Information Systems Security, Responsible AI, Security Awareness, Cloud Security, Vulnerability Assessments, and Threat Modeling

Generative AI and LLM Security

Course 213 hoursView course

What you'll learn

Identify key vulnerabilities and attack vectors in Generative and Agentic AI systems.
Apply strategies to secure AI training data, pipelines, and supply chains from risks.
Analyze LLM-specific threats and implement guardrails, safety, and ethical practices.
Evaluate ethical and regulatory compliance requirements for AI systems.

Skills you'll gain

Generative AI, Responsible AI, Data Ethics, Artificial Intelligence, Cloud Security, Cyber Attacks, Computer Security Awareness Training, Natural Language Processing, Governance Risk Management and Compliance, Artificial Intelligence and Machine Learning (AI/ML), Security Strategy, Threat Modeling, Network Security, Security Management, Supply Chain, LLM Application, Risk Management, Cyber Security Strategy, Cyber Security Policies, and Google Gemini

Securing AI Systems

Course 39 hoursView course

What you'll learn

Identify AI security concepts, attack types, and mitigation strategies.
Implement defenses, red-team simulations, and SOC/cloud/hardware security measures.
Evaluate weaknesses, assess defense effectiveness, and review incident response.
Design end-to-end secure AI systems and integrated security workflows.

Skills you'll gain

Artificial Intelligence and Machine Learning (AI/ML), Information Systems Security, MLOps (Machine Learning Operations), Penetration Testing, Threat Detection, Incident Response, Identity and Access Management, Security Strategy, Artificial Intelligence, Vulnerability Assessments, Security Engineering, Responsible AI, Hardening, Security Controls, Cybersecurity, Threat Modeling, Machine Learning, Cloud Security, Application Security, and Continuous Monitoring

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Edureka

98 Courses105,945 learners

Offered by

Edureka

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Frequently asked questions

Most learners complete the Specialization in 2–3 months with a suggested pace of 5–6 hours per week, though you can adjust the schedule to fit your availability.

You should have basic Python programming skills and familiarity with AI or machine learning concepts. No prior expertise in cybersecurity is required.

Yes, we recommend taking the courses in sequence, as each course builds upon concepts from the previous one, progressing from fundamentals to advanced security practices.

AI Security Specialization

What you'll learn

Overview

Skills you'll gain

Tools you'll learn

What’s included

Advance your subject-matter expertise