AI Security Learning Resources and Certifications

This comprehensive list of AI Security learning resources is organized by skill level and includes a mix of industry certifications, university courses, online bootcamps, workshops, and books. Each resource is labeled with its level (Beginner, Intermediate, Advanced), cost, focus (Practical, Theoretical, or Both), and whether a certification is offered. Resources from reputable institutions and platforms are ranked higher. Prompt engineering resources are highlighted and listed first, given their current importance in AI security.

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Beginner Level

ChatGPT Prompt Engineering for Developers – DeepLearning.AI (Coursera)

A short course created in collaboration with OpenAI that teaches how to write effective prompts for large language models. Covers two key principles for prompt writing and strategies to systematically engineer prompts, how LLMs work, best practices for prompting, and how to use LLM APIs for tasks like summarization, transformation, and chatbot development ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=Certifying%20Organization%3A%20DeepLearning)). This course is widely recognized as an accessible introduction to prompt engineering, taught by reputable instructors (DeepLearning.AI/Andrew Ng and OpenAI).

Google Prompting Essentials – Google (Coursera)

An introductory course by Google that teaches how to give clear and specific instructions to generative AI. Students learn effective prompting techniques for tasks such as crafting emails, brainstorming ideas, building tables, summarizing documents, and creating data visualizations ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=How%20to%20give%20clear%20and,world%20examples)). The course also addresses evaluating AI outputs for bias and errors, with hands-on exercises leading to a personal library of reusable prompts ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=How%20to%20give%20clear%20and,world%20examples)). No prerequisites are required, making it a popular starting point for prompt engineering basics.

AI Prompt Engineering for Beginners – Davidson College (edX)

A short hands-on course where learners use AI tools to produce and iterate on content. Participants create an AI-generated first draft and then refine it using prompting techniques, learning how to provide clear context and instructions for useful outputs ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=In%20this%20course%2C%20you%27ll%20produce,improve%20upon%20workflows%20with%20AI)). It covers daily productivity uses of AI (e.g., planning, content creation) and is ideal for newcomers looking to improve workflows with AI assistance ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=In%20this%20course%2C%20you%27ll%20produce,improve%20upon%20workflows%20with%20AI)). This course requires no prior knowledge and is part of Davidson College’s initiative on AI education.

AI Security & Governance Certification – Securiti

An on-demand course covering the foundations of AI security governance, offered by data security firm Securiti. Modules include introductions to Generative AI and AI governance, AI risk assessment, controlling data inputs/outputs, global AI laws, and regulatory compliance ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=AI%20Security%20%26%20Governance%20Certification)) ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,AI%20Governance%20Program%20and%20Management)). The program is concise (about 2 to 2.5 hours) and includes eight quizzes plus a certification exam ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=Eight%20quizzes%20and%20a%20certification,2.5%20hours)). It’s a non-technical overview aimed at professionals who need to understand AI risks, governance frameworks, and ethical considerations in deploying AI systems.

Ethics of AI – University of Helsinki (MOOC)

A free course that explores the ethical dimensions of Artificial Intelligence, including fairness, bias, and societal impact. Created by the University of Helsinki (as part of their Elements of AI series), it is intended for a broad audience interested in responsible AI development ([Ethics of AI](https://ethics-of-ai.mooc.fi/#:~:text=Ethics%20of%20AI%20The%20Ethics,the%20ethical%20aspects%20of%20AI)). The course examines real-world case studies of AI ethics and fairness, helping learners understand how ethical principles and security-related concerns (like misuse and bias) intersect. This MOOC is well-regarded for raising awareness of AI’s societal implications.

Intermediate Level

Prompt Engineering for ChatGPT – Vanderbilt University (Coursera)

An in-depth course (about 18 hours) on designing effective prompts, offered by Vanderbilt University. It introduces a variety of prompt patterns and advanced techniques, such as few-shot prompting, chain-of-thought reasoning, using one AI to evaluate another’s output, and complex prompt templates ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=An%20introduction%20to%20prompts%2C%20prompt,based%20application)). Learners practice combining these patterns (e.g. outline expansion, menu-based prompts, fact-checking prompts) to build a prompt-driven application ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=An%20introduction%20to%20prompts%2C%20prompt,based%20application)). Basic computer skills are the only prerequisite ([14 Top Prompt Engineering Certifications | VKTR](https://www.vktr.com/ai-upskilling/10-top-prompt-engineering-certifications/#:~:text=Requirements%3A%20Basic%20computer%20use)). Vanderbilt’s involvement and the comprehensive curriculum give this course a strong reputation for those seeking a deeper mastery of prompt engineering.

Introduction to Prompt Hacking – Learn Prompting (Maven Platform)

This course from the Learn Prompting community (instructor Sander Schulhoff) delves into the security vulnerabilities of large language models. It covers prompt hacking techniques such as prompt injection and jailbreaks, teaching learners how attackers exploit hidden model behaviors ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20course%20explores%20prompt%20hacking%2C,robust%20defenses%20for%20AI%20systems)). Participants also learn ethical considerations and basic defense strategies to secure AI systems ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20course%20explores%20prompt%20hacking%2C,robust%20defenses%20for%20AI%20systems)). Through interactive content and hands-on playground exercises, students gain practical experience identifying risks and safeguarding LLMs. This course is well-regarded in the AI red-teaming community and provides a bridge from basic prompting to adversarial prompt crafting.

IBM Generative AI for Cybersecurity Professionals – IBM (Coursera Specialization)

A three-course specialization by IBM that introduces generative AI concepts and then applies them to cybersecurity. The first course covers Generative AI fundamentals and use cases; the second focuses on Prompt Engineering basics and best practices; the third course ties it all together by exploring how generative AI can both enhance and threaten cybersecurity ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=The%20IBM%20Generative%20AI%20for,that%20includes%20the%20following%20courses)) ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,prevent%20attacks%20on%20GenAI%20models)). Topics include using GenAI for threat detection and incident response, as well as understanding GenAI-driven attacks and defenses ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,prevent%20attacks%20on%20GenAI%20models)). The specialization is self-paced with quizzes and projects, and provides a solid foundation for practitioners to “boost their cybersecurity career” with GenAI skills ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,and%20how%20to%20prevent%20attacks)). IBM’s name and the practical labs give it credibility for professional development.

Secure and Private AI – Meta & OpenMined (Udacity)

A hands-on course developed by Facebook (Meta) and OpenMined, teaching three cutting-edge techniques for privacy-preserving AI: federated learning, differential privacy, and encrypted computation ([Free Course: Secure and Private AI from Facebook | Class Central](https://www.classcentral.com/course/udacity-secure-and-private-ai-13642#:~:text=Information%20Security%20,Tags)). Learners gain experience using libraries like PySyft to implement privacy in machine learning workflows. The course assumes basic knowledge of machine learning and Python. It’s praised for providing practical skills in securing data and models, which is a critical aspect of AI security. Andrew Trask (OpenMined) leads the instruction, adding to its reputation. This free Udacity course offers a unique focus on data confidentiality in AI systems.

Securing AI and Advanced Topics – Johns Hopkins University (Online Course)

An instructor-led online course from JHU covering how AI is used in cybersecurity and how to secure AI systems. It explores advanced techniques like Generative Adversarial Networks (GANs) and reinforcement learning in a security context, and how to evaluate and harden AI models against threats ([Johns Hopkins University - Securing AI and Advanced Topics](https://lifelonglearning.jhu.edu/jhu-online-course-securing-ai-and-advanced-topics/#:~:text=This%20course%20covers%20advanced%20topics,AI%20models%20and%20their%20performance)). Students engage in hands-on activities, modifying AI algorithms in Python to understand adversarial attacks and defenses. The curriculum includes AI for fraud prevention in cloud services, concepts of adversarial attacks with GANs, and using reinforcement learning for cybersecurity applications ([Johns Hopkins University - Securing AI and Advanced Topics](https://lifelonglearning.jhu.edu/jhu-online-course-securing-ai-and-advanced-topics/#:~:text=,Image%3A%20skillSupervised%20Learning)). A foundational knowledge of Python/ML is expected ([Johns Hopkins University - Securing AI and Advanced Topics](https://lifelonglearning.jhu.edu/jhu-online-course-securing-ai-and-advanced-topics/#:~:text=learning%2C%20as%20well%20as%20evaluate,AI%20models%20and%20their%20performance)). This course is notable for being taught by JHU faculty and offering live seminars, lending academic rigor and credibility ([Johns Hopkins University - Securing AI and Advanced Topics](https://lifelonglearning.jhu.edu/jhu-online-course-securing-ai-and-advanced-topics/#:~:text=Securing%20AI%20and%20Advanced%20Topics)) ([Johns Hopkins University - Securing AI and Advanced Topics](https://lifelonglearning.jhu.edu/jhu-online-course-securing-ai-and-advanced-topics/#:~:text=Earn%20a%20certificate%20of%20completion,CEUs%29%20upon%20program%20completion)).

Certified AI Security Engineer – QA (APMG Accredited)

A comprehensive, hands-on training program by QA Ltd (UK) that prepares professionals to secure AI systems, culminating in an independent certification exam administered by APMG. The course covers a broad AI security landscape: understanding various AI systems and their vulnerabilities, secure integration of large language models (LLMs) into applications, safeguarding training data, and building robust AI infrastructure ([Top 10 AI Certifications You Can Earn in 2025 | QA](https://www.qa.com/en-us/browse/certifications/ai-certifications/#:~:text=By%20the%20end%20of%20this,the%20integrity%20of%20your%20systems)) ([Top 10 AI Certifications You Can Earn in 2025 | QA](https://www.qa.com/en-us/browse/certifications/ai-certifications/#:~:text=,Secure%20LLM%20Integration)). Specific attack techniques like prompt injection, model jailbreaks, model extraction, and adversarial examples are addressed along with mitigation strategies ([Top 10 AI Certifications You Can Earn in 2025 | QA](https://www.qa.com/en-us/browse/certifications/ai-certifications/#:~:text=,Secure%20LLM%20Integration)) ([Top 10 AI Certifications You Can Earn in 2025 | QA](https://www.qa.com/en-us/browse/certifications/ai-certifications/#:~:text=%2A%20Understanding%20and%20Countering%20AI,AI%20Interaction)). By course end, participants learn to protect AI assets and maintain system integrity in real-world scenarios ([Top AI Certifications - 2025 - QA](https://www.qa.com/en-us/browse/certifications/ai-certifications/#:~:text=Top%20AI%20Certifications%20,and%20maintain%20the%20integrity)). This certification is relatively new but backed by APMG’s credibility and QA’s industry experience, making it a notable credential for AI security engineers.

MLSecOps Foundations – Protect AI

A course focused on securing machine learning pipelines and deployments (the emerging field of “MLSecOps”). Authored by industry experts at Protect AI (led by CISO Diana Kelley), it teaches participants how to weave security throughout the ML lifecycle ([MLSecOps Certification Sign In](https://protectai.com/mlsecops-foundations-certification#:~:text=Course%20author%2C%20Diana%20Kelley%2C%20CISO,woven%20into%20the%20ML%20pipeline)) ([MLSecOps Certification Sign In](https://protectai.com/mlsecops-foundations-certification#:~:text=models%2C%20conduct%20AI,ML%20systems%20against%20evolving%20threats)). Topics include conducting AI-specific threat assessments, monitoring the ML supply chain for vulnerabilities, implementing incident response for AI systems, and integrating DevSecOps practices into MLOps workflows ([MLSecOps Certification Sign In](https://protectai.com/mlsecops-foundations-certification#:~:text=you%E2%80%99ll%20learn%20effective%20strategies%20to,woven%20into%20the%20ML%20pipeline)). By the end, learners understand strategies to proactively secure ML models and infrastructure against evolving threats ([MLSecOps Certification Sign In](https://protectai.com/mlsecops-foundations-certification#:~:text=central%20to%20our%20lives%2C%20ensuring,powered%20world)) ([MLSecOps Certification Sign In](https://protectai.com/mlsecops-foundations-certification#:~:text=Throughout%20the%20course%2C%20learners%20will,ML%20systems%20against%20evolving%20threats)). This course is highly practical, aligning with real-world MLSecOps frameworks, and offers a certificate that demonstrates knowledge of secure AI engineering practices.

Certified Generative AI in Cybersecurity – GSDC

Offered by the Global Skill Development Council, this program is designed for professionals (like security leads, CIOs/CTOs) to master generative AI from a cybersecurity perspective. It covers foundations of generative AI and core cybersecurity, then dives into specific genAI techniques: Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) and how they can be used or misused ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=This%20program%20from%20the%20Global,syllabus%20includes%20the%20following%20modules)), deep reinforcement learning in cyber contexts, and security & ethical considerations of AI ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=This%20program%20from%20the%20Global,syllabus%20includes%20the%20following%20modules)) ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,on%20Demos)). The curriculum includes hands-on demos and a capstone project applying generative AI tools to real security scenarios ([Top AI security certifications to consider | TechTarget](https://www.techtarget.com/searchsecurity/tip/Top-AI-security-certifications-to-consider#:~:text=,on%20Demos)). The program concludes with a 40-question exam. This certification is relatively niche but demonstrates expertise in the intersection of genAI and cybersecurity. It’s recognized by GSDC, an international certification body.

Advanced Level

Advanced Prompt Hacking – Learn Prompting (Maven Platform)

An advanced course targeting experienced prompt engineers, developers, and AI security researchers. Taught by Sander Schulhoff, it covers cutting-edge prompt exploitation techniques such as sophisticated prompt injections, multi-stage jailbreaks, and cognitive hacking strategies against LLMs ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20course%20explores%20the%20forefront,LLMs)). Participants get hands-on practice crafting complex attack prompts and learn to assess and patch LLM vulnerabilities. Defensive strategies are also discussed to help secure models from these advanced exploits ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20course%20explores%20the%20forefront,LLMs)). This course is highly regarded in the AI red-teaming community and is a follow-up to the introductory prompt hacking course, pushing learners to the forefront of prompt-based attack and defense methods.

AI Red-Teaming and AI Safety Masterclass – Learn Prompting (Maven)

An intensive masterclass for professionals (AI security specialists, product managers, etc.) to gain expert-level red teaming skills for generative AI systems ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=,Teaming%20and%20AI%20Safety%3A%20Masterclass)). Led by Sander Schulhoff, this course provides hands-on experience in identifying and exploiting vulnerabilities in AI models, including prompt injections, jailbreaking, and adversarial attacks on image and text models ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20masterclass%20teaches%20you%20the,or%20your%20own%20AI%20model)). Learners practice on a dedicated platform (e.g., HackAPrompt) to attack and defend AI systems, and the curriculum covers designing defense mechanisms and aligning models with security standards ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20masterclass%20teaches%20you%20the,or%20your%20own%20AI%20model)). The capstone involves exposing vulnerabilities in a live chatbot or one’s own AI model, bringing together all learned skills in a real project ([Top 8 Online AI Red Teaming Courses [Free & Paid]](https://learnprompting.org/blog/ai-red-teaming-courses?srsltid=AfmBOooBZvDy4UCM3naVUnQ024trGiX1alNe4H_Hj5fb9yK3-pd0a7lH#:~:text=This%20masterclass%20teaches%20you%20the,or%20your%20own%20AI%20model)). With its high-profile instructor and practical focus, this masterclass is viewed as a top-tier training for AI red teamers.

Certified AI Security Professional (CAISP) – Practical DevSecOps

A comprehensive certification course that equips professionals to secure AI/ML systems across their lifecycle. The curriculum begins with an overview of unique security risks in AI – including adversarial ML, data poisoning, and AI misuse ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=We%20start%20with%20an%20overview,computer%20vision%2C%20and%20autonomous%20systems)) – then addresses security for different AI applications (NLP, computer vision, autonomous systems) ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=We%20start%20with%20an%20overview,computer%20vision%2C%20and%20autonomous%20systems)). Learners engage in hands-on labs tackling model inversion attacks, evasion attacks, and the dangers of public datasets/models ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=The%20Certified%20AI%20Security%20Professional,assess%2C%20and%20mitigate%20these%20risks)) ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=Through%20hands,integrity%2C%20and%20protecting%20AI%20infrastructure)). The course also covers securing AI supply chains: protecting data pipelines, ensuring model integrity, and implementing secure AI development techniques like differential privacy and federated learning ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=In%20the%20final%20sections%2C%20you%E2%80%99ll,and%20robust%20AI%20model%20deployment)). Finally, it maps AI risks to frameworks like MITRE ATLAS to provide a structured approach to risk management ([Certified AI Security Professional - AI Security Certification - Practical DevSecOps](https://www.practical-devsecops.com/certified-ai-security-professional/#:~:text=In%20the%20final%20sections%2C%20you%E2%80%99ll,and%20robust%20AI%20model%20deployment)). After training, students prove their skills in a rigorous 6-hour practical exam to earn the CAISP credential. This program is one of the first of its kind, and Practical DevSecOps (with a track record in DevSecOps training) has earned respect for its hands-on, lab-driven approach ([Pricing - Practical DevSecOps](https://www.practical-devsecops.com/pricing/#:~:text=Certified%20AI%20Security%20Professional%20,CCSE)).

Adversarial Machine Learning Training – HiddenLayer (2-Day Workshop)

An intensive training for data scientists and security teams to understand and counter adversarial machine learning tactics. Over two days, participants learn about various TTPs (Tactics, Techniques, and Procedures) used to attack ML models and the most effective countermeasures ([Adversarial Machine Learning Training • HiddenLayer • Accredible • Certificates, Badges and Blockchain](https://certifications.hiddenlayer.com/group/567459#:~:text=Two,CleverHans%2C%20Augly%2C%20Foolbox%2C%20and%20more)). The course provides an overview of offensive AI tooling – including open-source libraries like IBM's Adversarial Robustness Toolbox (ART), Microsoft Counterfit, CleverHans, Foolbox, etc. – and teaches how to use them to simulate attacks (e.g., evasion, model poisoning, model stealing) ([Adversarial Machine Learning Training • HiddenLayer • Accredible • Certificates, Badges and Blockchain](https://certifications.hiddenlayer.com/group/567459#:~:text=Two,CleverHans%2C%20Augly%2C%20Foolbox%2C%20and%20more)) ([Adversarial Machine Learning Training • HiddenLayer • Accredible • Certificates, Badges and Blockchain](https://certifications.hiddenlayer.com/group/567459#:~:text=countermeasures%20to%20protect%20against%20them,CleverHans%2C%20Augly%2C%20Foolbox%2C%20and%20more)). Learners also discover how to integrate adversarial testing into their internal ML model review processes ([Adversarial Machine Learning Training • HiddenLayer • Accredible • Certificates, Badges and Blockchain](https://certifications.hiddenlayer.com/group/567459#:~:text=Two,CleverHans%2C%20Augly%2C%20Foolbox%2C%20and%20more)). HiddenLayer, a firm specializing in ML security, issues a digital certificate via Accredible upon completion. This workshop is highly regarded among enterprises for its practical, tool-driven focus on ML attack and defense.

AI Security Level 3 – AI Certs (Advanced Cyber Defense & Risk Management)

An advanced certification program focused on leadership in AI-driven cyber defense. It prepares learners to counter AI-powered cyber threats and manage AI-related security risks at an organizational level. The curriculum includes using AI for threat detection and predictive defense, implementing adversarial AI defenses and secure AI system design, and exploring “Zero Trust” frameworks for AI environments ([AI Security Level 3 - AICERTs - Empower with AI Certifications](https://www.aicerts.ai/certifications/security/ai-security-3/#:~:text=%2A%20AI,reach%20%24133%20billion%20by%202030)) ([AI Security Level 3 - AICERTs - Empower with AI Certifications](https://www.aicerts.ai/certifications/security/ai-security-3/#:~:text=What%20will%20I%20learn%20in,this%20course)). A key component is a hands-on capstone project where candidates apply concepts to secure an AI system (integrating AI with areas like blockchain or cloud security) ([AI Security Level 3 - AICERTs - Empower with AI Certifications](https://www.aicerts.ai/certifications/security/ai-security-3/#:~:text=You%20will%20learn%20how%20AI,on%20capstone%20project)). Basic coding (Python) is recommended to follow the technical portions, but support resources are provided ([AI Security Level 3 - AICERTs - Empower with AI Certifications](https://www.aicerts.ai/certifications/security/ai-security-3/#:~:text=reliability)). The certification leverages AI-enhanced proctoring and blockchain verification for exam integrity ([AI Security Level 3 - AICERTs - Empower with AI Certifications](https://www.aicerts.ai/certifications/security/ai-security-3/#:~:text=Image%3A%20Certificate%20Image%3A%20Certificate)). AI Certs is a newer certification body, but this Level 3 program signals a comprehensive mastery of AI security and governance for professionals aiming to lead in this space.

AI for Cybersecurity Specialization – Johns Hopkins University (Coursera)

A specialized program by JHU that trains learners to apply AI techniques to solve complex cybersecurity problems. It covers AI-driven fraud detection, malware analysis, anomaly detection in networks, and the implications of advanced AI methods like Generative Adversarial Networks in security ([AI for Cybersecurity | Coursera](https://www.coursera.org/specializations/ai-for-cybersecurity#:~:text=Specialization%20)). The courses emphasize hands-on projects: for example, building machine learning and deep learning models to detect IoT botnet activity in network traffic, and developing a metamorphic malware detector using Hidden Markov Models ([AI for Cybersecurity | Coursera](https://www.coursera.org/specializations/ai-for-cybersecurity#:~:text=In%20the%20,demonstrations%20along%20with%20their%20code)). These projects require exporting and testing models on real data, with deliverables including code and video demos ([AI for Cybersecurity | Coursera](https://www.coursera.org/specializations/ai-for-cybersecurity#:~:text=In%20the%20,driven%20threat)). Through the specialization, students also learn how to evaluate model performance under adversarial conditions and reinforce models against attacks ([AI for Cybersecurity | Coursera](https://www.coursera.org/specializations/ai-for-cybersecurity#:~:text=explore%20advanced%20techniques%20for%20detecting,With%20a)). Earning this certificate demonstrates advanced competency in using AI to defend against cyber threats, backed by JHU’s academic excellence.

Explainable AI (XAI) Specialization – Duke University (Coursera)

A three-course specialization focused on building ethical and transparent AI systems ([Explainable AI (XAI) Specialization - Coursera](https://www.coursera.org/specializations/explainable-artificial-intelligence-xai#:~:text=Explainable%20AI%20%28XAI%29%20Specialization%20,and%20ethical%20AI%20development)). It covers fundamental concepts of explainability and interpretability in AI, techniques for developing interpretable machine learning models, and advanced methods to explain complex models (like neural networks). Topics include SHAP values, LIME, model-agnostic interpretability, and how to incorporate fairness and accountability into AI systems. Duke also emphasizes ethical AI development throughout the courses ([Explainable AI (XAI) Specialization - Coursera](https://www.coursera.org/specializations/explainable-artificial-intelligence-xai#:~:text=Offered%20by%20Duke%20University,and%20ethical%20AI%20development)). While not exclusively about security, XAI is crucial for auditing AI models and detecting anomalous or biased behavior, which ties into secure and fair AI deployment. This specialization is taught by Duke faculty and provides a strong academic grounding in XAI, useful for professionals who need to audit or validate AI models in sensitive applications.

Adversarial Machine Learning – A. Joseph, B. Nelson, B. Rubinstein, J. Tygar (Book)

An authoritative textbook (Cambridge University Press, 2018) that provides a complete introduction to making machine learning robust against adversaries. Written by leading researchers from UC Berkeley and University of Melbourne, it covers the taxonomy of attacks on ML (evasion, poisoning, inference), theoretical foundations of adversarial learning (game theory, robust statistics), and algorithms for defending models. Readers will learn how ML systems can adapt when an adversary actively poisons or manipulates data, and the latest techniques for investigating and improving model security ([Adversarial Machine Learning: 9781107043466: Computer Science Books @ Amazon.com](https://www.amazon.com/Adversarial-Machine-Learning-Anthony-Joseph/dp/1107043468#:~:text=Written%20by%20leading%20researchers%2C%20this,preserving)). The book also surveys privacy-preserving machine learning and future research directions. This is a highly recommended reading for advanced practitioners or researchers; while dense, it bridges academic research with practical insights on designing effective countermeasures to modern ML attacks ([Adversarial Machine Learning: 9781107043466: Computer Science Books @ Amazon.com](https://www.amazon.com/Adversarial-Machine-Learning-Anthony-Joseph/dp/1107043468#:~:text=Written%20by%20leading%20researchers%2C%20this,preserving)).

Machine Learning Security Principles – John Paul Mueller (Book)

A practitioner-oriented guide (Packt Publishing, 2022) that explores the critical aspects of securing machine learning systems. It serves as a training manual on how to be responsible with data and models in real-world AI applications ([Machine Learning Security Principles: Keep data, networks, users ...](https://www.amazon.com/Machine-Learning-Security-Principles-applications/dp/1804618853#:~:text=...%20www.amazon.com%20%20,The)). Key topics include protecting data confidentiality, ensuring integrity of training data (preventing poisoning), model deployment security, monitoring for adversarial activity, and implementing governance and compliance measures for AI. The book provides hands-on examples and best practices, making it a useful resource for engineers who want to apply security measures in the ML pipeline. While not as deep in theory as academic texts, it is highly informative and filled with practical advice on keeping AI models safe from prying eyes and attacks ([Machine Learning Security Principles: Keep data, networks, users ...](https://www.amazon.com/Machine-Learning-Security-Principles-applications/dp/1804618853#:~:text=...%20www.amazon.com%20%20,The)). John P. Mueller is an experienced technical author, which contributes to the book’s clarity and approachability.