Course: Leading Security Teams for GenAI Solutions
duration: 15 hours |
Language: English (US) |
access duration: 180 days |

Details
This course offers a comprehensive exploration of leading security teams for generative AI solutions. You'll start this course by delving into enhancing security posture by monitoring and leveraging emerging generative AI technologies, defending against IP infringement, and implementing governance and security measures. Next, you will learn about the intersection of generative AI with common security threats and cybersecurity applications, you'll craft effective defence strategies and leverage machine learning for enhanced security. Through a focus on intellectual property protection, you'll grasp detection techniques, legal considerations, and future trends in IP safeguarding. You'll also explore governance best practices, regulatory compliance, and the benefits of AI auditing to ensure ethical AI usage. Lastly, delving into security implications, you'll counteract security attacks, manage ethical concerns, and enhance protection controls to safeguard AI systems effectively.
Result
After completing this course, you’ll recognize how to monitor and utilize emerging generative AI technologies to help improve an organization’s overall security posture including intellectual property.
Prerequisites
No formal prerequisites. Experience in the field is a plus.
Target audience
Manager, Team Leader
Content
Leading Security Teams for GenAI Solutions
Leading Security Teams for GenAI Solutions: Enhancing Security Posture
Enhancing your security posture is an essential part of protecting yourself against generative artificial intelligence (AI) technologies. Monitoring and leveraging emerging generative AI technologies help organizations stay safe and secure while reducing manual work. In this course, discover why enhancing security posture is important, common security and cyber threats organizations are facing today, and the applications and advantages of using AI in cybersecurity. Next, examine the components of a successful cyberattack defense strategy and how to leverage machine learning (ML) in cybersecurity. Lastly, explore AI cybersecurity considerations and possible future trends of AI in cybersecurity. Upon course completion, you'll recognize how to monitor and utilize emerging generative AI technologies to help improve an organization's overall security posture.
Leading Security Teams for GenAI Solutions: Protecting Intellectual Property
Protecting intellectual property (IP) is an important part of any business. In this course, you will learn the fundamentals of intellectual property including copyright, trademarks, patents, and trade secrets. Discover how to defend against intellectual property infringement in the realm of generative AI, how using generative AI can result in IP infringement, and considerations to have when using generative AI solutions for yourself or your business. Then you will learn how to detect when your intellectual property has been infringed upon, identify risk areas, and determine what detection tools are available. Finally, you will explore legal considerations surrounding intellectual property and AI and investigate future trends of intellectual property in the era of AI. After completing this course, you will be ready to the crucial steps to detect and protect the intellectual property within your organization.
Leading Security Teams for GenAI Solutions: Generative AI Governance
Generative artificial intelligence (AI) creates a variety of concerns in a number of different ways, so we must create governance to regulate these concerns. In this course, you will discover why governance in the realm of generative AI is crucial, how and by whom governance can be achieved, as well as the challenges and opportunities that arise with the use of generative AI. In addition, you will also explore how governments and legal bodies can regulate generative AI, and what regulations are already in place in the public sector. Then you will examine AI governance best practices, including engaging stakeholders, managing AI models, and building internal governance structures. Next, you will investigate the benefits of AI auditing and monitoring. Finally, you will learn how to implement a governance approach that includes user education, data and AI risk management, and regulatory compliance.
Leading Security Teams for GenAI Solutions: Use of Generative AI
When using generative artificial intelligence (AI) content within your business, you need to know how to leverage it safely and effectively. In this course, you will learn about techniques used to identify AI-generated content and how to avoid possible misinformation that it can produce. You will investigate deepfakes and learn how to detect them. You will discover how to provide proper attribution when using generative AI content and how to avoid having any copyright issues. Next, you will explore industry use cases for generative AI, and more specifically, discover common use cases for boosting cybersecurity using generative AI. Then you will examine stakeholder considerations and possible generative AI challenges. Finally, you will focus on security protections, security risks, and mitigating risks associated with generative AI. Upon course completion you will be able to confidently take steps to secure your organization when using generative AI solutions.
Leading Security Teams for GenAI Solutions: Security Implications
The introduction of generative AI has created security, privacy, ethical, and moral implications for everyone involved. In this course, you will learn how and why generative AI is being used in security attacks, how to put countermeasures in place to defend against these attacks, and how to navigate and mitigate those attacks from happening. You will also explore the ethical and moral concerns that generative AI has created, how privacy plays a role in those concerns, and how to manage those risks. Then you will discover how generative AI can be leveraged by threat actors to perform data breaches, create malware threats, and coordinate social engineering attacks. Next, you will investigate how generative AI can be used maliciously to perform model manipulation and data poisoning. Finally, you will examine how to enhance protection controls using processes, governance, and ethics, and focus on common considerations for securing AI systems.
Final Exam: Generative AI Security Considerations
Final Exam: Generative AI Security Considerations will test your knowledge and application of the topics presented throughout the Generative AI Security Considerations track.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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