Machine Learning for Cybersecurity (MERIT)

This course bridges the gap between Machine Learning (ML) and cybersecurity, focusing on how ML algorithms can be utilised to fortify cybersecurity measures and applications. Designed by UPC - Universitat Politècnica de Catalunya, the course is part of the MERIT project, supported by the Digital Europe Programme of the European Union. MERIT is a European initiative aimed at addressing this gap by equipping the next generation of experts with the knowledge and skills needed to thrive in these critical areas. 

About this course 

The course covers the entire process of applying ML models to detect anomalies, predict attacks, and automate threat intelligence. Students will learn about the challenges and opportunities of applying ML in a cybersecurity context, including ethical considerations and the need for robust, secure ML models as there are many security applications which have large amount of data related to the system as well as adversarial actions. 

Throughout this course, students will learn the theoretical concepts during the lectures as exploring different problem domains, gain hands-on experience to build up their skills by practicing on assignments, and finally demonstrate their knowledge and skills by participating in a final project to identify the type of machine learning algorithms that are useful for specific security applications and how to improve the defence against attacks to ultimately anticipate the potential attack variants that may rise in the future.

Learning outcomes

Upon successful completion of this course, students will be able to: 

• Identify the main principles and approaches for natural language processing and delve into other, similar challenges. 
• Learn to apply machine learning algorithms and models in cybersecurity problems and develop tools to boost cyber defence practices. 

Find out more about this course via this guide and on the course's dedicated webpage.