Data Science For Cybersecurity


Data Science For Cybersecurity

Facultad de Ingeniería
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This course aims at preparing the students to handle the massive shifts in technology and operations, driven by data science, that cybersecurity is undergoing. It will overview how to extract security incident patterns (or insights) from cybersecurity data and build corresponding data-driven models, two key aspects to make security systems automated and intelligent. This course starts briefly overviewing the motivation and concepts of cybersecurity and data science, next it presents the relevant methods/technologies to understand the applicability of cybersecurity data science towards data-driven intelligent decision-making in cybersecurity, the main approaches for security data gathering and preparing, a discussion on different machine learning and statistical learning tasks in cybersecurity, multi-layered frameworks for smart cybersecurity services, cybersecurity testbeds and datasets. This course is enriched with real case studies and the students will be able to prepare their main hands-on projects to put in practice their knowledge.

Regular students at the University (students who are studying for an undergraduate or graduate degree) will not be able to register through the Educación Continua for this course. In case of registration, the Management will proceed with its return.


Successful students will be able to:

  • Have a clear overview about cybersecurity concepts, data science and the application of data science to different context of cybersecurity;
  • Understand the challenges and directions in cybersecurity considering the Internet of things (IoT) context and the application of data science;
  • Understand the security challenges and existing security mechanisms against security threats in cloud computing using data science;
  • Have a strong comprehension about the application and the potential of artificial intelligence and data science to cybersecurity.

Successful students will be able to:

  • Introduction to Cybersecurity
  • Introduction to Cybersecurity
  • Data Visualization
  • Network and System Protection
  • Artificial Intelligence and Machine Learning applied to cybersecurity
  • Data preprocessing
  • Case studies in Cybersecurity


Michele Nogueira

Michele Nogueira Michele Nogueira is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), Brazil. She received her doctorate in Computer Science from the University Pierre et Marie Curie – Sorbonne Université, France. Her research focuses on network security, resilience, network management, and wireless and advanced networks, with an emphasis on building security science, cognitive networks, and predictive models. Body of research work includes areas as the Internet of Things (IoT), Cyber-Human Systems (CHS), cognitive radios, ad hoc networks, software-defined networks, vehicular networks, DDoS attacks mitigation and prediction, and survivability. Today, her research focuses on creating network security intelligence supported by data science. Dr. Nogueira was one of the pioneers in addressing survivability issues in self-organized wireless networks, being the work “A Survey of Survivability in Mobile Ad Hoc Networks”, one of her prominent scientific contributions.


Eventualmente la Universidad puede verse obligada, por causas de fuerza mayor a cambiar sus profesores o cancelar el programa. En este caso el participante podrá optar por la devolución de su dinero o reinvertirlo en otro curso de Educación Continua que se ofrezca en ese momento, asumiendo la diferencia si la hubiere.

La apertura y desarrollo del programa estará sujeto al número de inscritos. El Departamento/Facultad (Unidad académica que ofrece el curso) de la Universidad de los Andes se reserva el derecho de admisión dependiendo del perfil académico de los aspirantes.