Aperçu du cours
This pioneering course blends the domains of cyber security and artificial intelligence. It has been designed for cyber security professionals who want to understand and implement AI models for exploring logs, security events, and other types of data. Classifying analytics is especially encouraged as well as NLP and Image Recognition techniques based on types of data sources found in the cybersecurity domain.
Where coding is needed, Python and some selected libraries will be used. The expected audience is expected to be familiar with scripting coding but is not required to master any specific language.
Prérequis
- Python or similar scripting language (like R, Matlab, etc)
- Notions in AI/Machine Learning
Fonctionnalités
- Understand the concepts of AI, ML and DL. Their strengths and limitations
- Generate different visualisations of your data by applying statistical models to real cybersecurity problems in meaningful ways
- Familiarise with ML frameworks and methods
- Identify the best suited ML models to solve complex problems
- Work in specific cybersecurity use cases while being supervised by an AI expert
Public ciblé
- Engineers
- Developers
Détails
- 20 Sections
- 49 Lessons
- 5 Days
Expand all sectionsCollapse all sections
- Introduction to AI, ML & DL4
- Sample Toy Study2
- AI Frameworks1
- Framework Setup & Workshop2
- Introduction to NLP6
- Classification & Clustering2
- NLP Sample Toy Study1
- Interactive Discussion1
- Additional Supervised & Unsupervised methods3
- AI in Cybersecurity2
- NLP Applied to Cybersecurity5
- Use Case 12
- Interactive Discussion1
- Statistical Methods in ML3
- Examples2
- More Statistics3
- Case 1 (Continuation)2
- AI in Cybersecurity (part 2)3
- Use Case 22
- Revision & Closing2
Instructeur
