The theorical material can be found here.
Follow the instructions bellow:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txtThe notebooks can be found here
Can find the spreadsheet here.
| Date | Class | Topic |
|---|---|---|
| 20-09-2025 | 1 | Class Presentation |
| 27-09-2025 | 2 | SPAM Detector |
| 04-10-2025 | 3 | |
| 11-10-2025 | 4 | |
| 18-10-2025 | 5 | Anomaly Detection |
| 25-10-2025 | 6 | |
| 01-11-2025 | 7 | |
| 08-11-2025 | 8 | Mid-term Exam |
| 15-11-2025 | 9 | Malware Analysis |
| 22-11-2025 | 10 | |
| 29-11-2025 | 11 | |
| 06-12-2025 | 12 | Project |
| 13-12-2025 | 13 | |
| 20-12-2025 | 14 |
- S. Halder and S. Ozdemir, Hands-On Machine Learning for Cybersecurity: Safeguard your system by making your machines intelligent using the Python ecosystem. Packt Publishing Ltd, 2018.
- C. Chio and D. Freeman, Machine Learning and Security. O’Reilly, 2018.
- A. Parisi, Hands-On Artificial Intelligence for Cybersecurity: Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies. Packt Publishing Ltd, 2019.
- E. Tsukerman, Machine Learning for Cybersecurity Cookbook. Packt Publishing Ltd, 2019.
- J. P. Mueller and R. Stephens, Machine Learning Security Principles. Packt Publishing Ltd, 2019.
- Mário Antunes - mariolpantunes
This project is licensed under the MIT License - see the LICENSE file for details