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Cybersecurity in the Age of AI
The rise of cyber threats and generative AI has redefined cybersecurity, introducing tools to detect and respond to risks with precision. Yet, a critical expertise gap persists, as many professionals lack the training to integrate AI responsibly. Bridging this gap is essential for organizations to build resilience, manage risks, and secure their future in a high-stakes digital world.
This live online course, led by MIT AI experts Prof. John R. Williams and Dr. Abel Sanchez, equips professionals with the knowledge and skills to navigate cybersecurity challenges in an AI-driven landscape. Through interactive modules, live sessions, and hands-on activities, participants will explore foundational cybersecurity principles and cutting-edge AI-powered strategies for risk management, threat detection, and incident response.
63%
of security professionals see AI as key to enhancing threat detection and response.
Source: Cloud Security Alliance
3.4 Million
The global shortage of cybersecurity professionals, highlighting a critical skills gap.
Source: ISC2
70%
of cybersecurity professionals say AI proves highly effective for detecting threats that previously would have gone unnoticed.
Source: Ponemon Institute
A live online course to master AI-driven cybersecurity strategies
MIT Professional Education’s Cybersecurity in the Age of AI course equips professionals with the knowledge and skills needed to address modern security challenges in an AI-driven world. Participants will learn to prevent, detect, and respond to evolving threats while exploring the groundbreaking opportunities AI brings to the field. Through this course, professionals will gain practical insights into leveraging AI to strengthen cybersecurity frameworks and stay ahead in the rapidly shifting digital landscape.
Live Sessions Content
The Cybersecurity in the Age of AI program offers a dynamic blend of self-paced online modules and live faculty-led sessions. Each week, participants explore key concepts through engaging online content, hands-on activities, and case studies, then apply their knowledge in interactive 90-minute live sessions. With real-time discussions and expert insights, this format ensures participants gain practical skills to tackle cybersecurity challenges using AI-powered tools.
Module 1: Cybersecurity Foundations in the Digital Age
Live Session 1: Introduction to Cybersecurity Fundamentals and Best Practices
The first live session establishes the foundational knowledge required for navigating cybersecurity challenges in the digital age. Participants will delve into the fundamentals of information security, explore the current cyber threat landscape, and identify basic defensive strategies to protect critical systems.
- Understand the core principles of information security
- Analyze the cyber threat landscape and its implications for organizations
- Explore basic strategies for defending against cyber threats, including AI-enhanced approaches
Online Module 1: Essential Cybersecurity Concepts
Our first online module deepens your understanding of cybersecurity through practical and theoretical insights. With a focus on network security and threat management, you will engage with interactive content and apply their knowledge through a real-world case study.
- Learn the basics of network security, including common threat vectors
- Examine strategies for intrusion prevention and effective response
- Complete a case study analysis of a major cybersecurity breach, highlighting both traditional and AI-driven solutions
Module 2: Generative AI and Threat Detection
Live Session 2: AI-Powered Threat Detection and Mitigation
This session explores the transformative role of generative AI in cybersecurity. You will learn how AI models assist in identifying patterns within cyber threats and proactively mitigating risks. The session will also cover real-world applications of AI in detecting malware, identifying anomalies, and generating predictive threat intelligence.
- Understand the role of generative AI in modern cybersecurity
- Analyze applications of AI in malware detection and anomaly identification
- Explore how AI contributes to predictive threat intelligence for proactive defens
Online Module 2: AI-Driven Security Tools
The second online module of this course provides a comprehensive overview of AI models utilized in cybersecurity, with a focus on their application in threat detection and response. Participants will also engage in hands-on activities to gain practical experience deploying AI-powered tools.
- Learn about AI models in cybersecurity, including neural networks and deep learning techniques for pattern recognition
- Explore real-world use cases of AI in network traffic analysis
- Complete a practical lab exercise by setting up a simulated environment to analyze network traffic using AI tools
Module 3: Privacy, Ethics, and Compliance in AI-Enhanced Cybersecurity
Live Session 3: Privacy and Ethical Challenges with AI in Cybersecurity
This session addresses the critical issues of privacy, ethics, and compliance in the context of AI-enhanced cybersecurity. Participants will explore the challenges of balancing innovation with regulatory requirements and ethical practices. Key topics include GDPR, global data privacy standards, and the implications of AI decision-making in cybersecurity operations.
- Understand the ethical challenges of using AI in cybersecurity
- Analyze privacy issues and the role of regulations like GDPR in governing AI applications
- Explore the impact of AI decision-making on compliance and ethical practic
Online Module 3: Legal and Ethical Foundations
This online module delves into the intersection of cyber law, intellectual property, and privacy protection, providing participants with a strong foundation in the legal and ethical aspects of cybersecurity. The module will conclude with a hands-on assignment focused on crafting policies aligning with ethical considerations and legal requirements.
- Learn the basics of cyber law and its relevance to AI-enhanced cybersecurity
- Explore intellectual property issues related to digital security
- Draft an ethical cybersecurity policy for an AI-integrated organization
Module 4: Incident Response and Business Continuity with AI
Live Session 4: AI in Incident Response and Recovery
The last live session explores how AI transforms incident response and recovery processes in cybersecurity. You will examine the role of AI in rapid response, containment, and post-incident analysis, enabling organizations to minimize impact and ensure swift recovery. Real-world examples will highlight AI’s contribution to response planning, real-time data analysis, and proactive business continuity strategies.
- Understand the role of AI in incident response and containment
- Analyze real-time data for efficient incident management
- Explore proactive continuity planning enhanced by AI insigh
Online Module 4: Cyber Incident Analysis
Our last online module focuses on the practical application of AI-driven tools in the various stages of incident management. Participants will engage in a scenario-based simulation to develop hands-on skills in managing cyber incidents effectively while minimizing business disruption.
- Learn the key steps of incident detection, containment, eradication, and recovery
- Explore the application of AI-driven insights in incident analysis
- Complete a scenario-based simulation of an AI-supported incident respons
The skills you will develop
1.
Discover foundational cybersecurity principles and frameworks.
2.
Analyze AI’s transformative impact on cybersecurity strategies.
3.
Evaluate the ethical, privacy, and compliance challenges associated with AI.
4.
Implement generative AI tools to enhance security protocols and incident response.
5.
Examine the critical role of policy in shaping effective cyber defense frameworks.
6.
Prevent & mitigate business disruptions by leveraging AI-driven incident response strategies.
In addition, you will receive a Certificate of Completion
All participants who successfully complete this course will receive a MIT Professional Education Certificate of Completion. In addition, they will also earn 3.2 Continuing Education Unit (MIT CEUs).
To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.
*The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.
To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly
This course is aimed at
- IT Managers and Security Leaders who oversee cybersecurity operations and are exploring AI tools to strengthen their security posture.
- Executives and Decision-Makers responsible for organizational risk management, data protection, and strategic cybersecurity initiatives.
- Cybersecurity Analysts and Engineers looking to integrate generative AI into threat detection, incident response, and other security functions.
- Compliance and Legal Professionals who need a solid understanding of AI-related cybersecurity risks, ethical considerations, and regulatory implications.
Meet the instructors of this course
* speakers and topics are subject to change without notice.
Dr. Sanchez is the architect of the global network “The Internet of Things” and data analysis platforms for SAP, Ford, Johnson & Johnson, Accenture, Shell, Exxon Mobil and Altria. In cyber security, he has developed cyber-attack impact analyses for the U.S. Department of Defense and a password firewall for the IARPA.
Dr. Sanchez holds a Ph.D. from the Massachusetts Institute of Technology (MIT) and teaches MIT courses in cyber security, engineering, blockchain, and data science. He has been involved in developing educational software for Microsoft and establishing the Accenture Technology Academy. He has produced over 150 educational videos, has 10 years of experience with learning management systems, and has made deployments in the Americas, Asia, and Europe.
Professor John R. Williams’ research focuses on the development and application of computing algorithms in distributed cyberphysical systems. He was director of the Auto-ID Laboratory, where the Internet of Things was invented. He is considered, along with Bill Gates and Larry Ellison, one of the 50 most powerful people in “Computer Networks”.
He is author and coauthor of more than 250 articles in journals and conferences. Professor Williams teaches courses on the basics of programming, modern software development, the architecture of web, cloud and the blockchain systems.
