Data Science Cybersecuity Implementation

🚀 Course Title: Data Science Cybersecurity Implementation 🛡️

Course Headline: Case Studies of Cybersecurity with Machine Learning using Python

Dive into the intersection of data science and cybersecurity! This comprehensive course, led by the expert instructor Amine Mehabli, explores the latest advancements in cybersecurity through machine learning with a focus on practical case studies. 🧠💻

Course Description:

Machine learning is revolutionizing cybersecurity, and this course will equip you with the knowledge and skills to harness its power effectively. We'll tackle some of the most pressing issues in cybersecurity—malware, anomaly detection, SQL injection, credit card fraud, bots, spams, and phishing—by analyzing real-world case studies. Through these examples, you'll understand how machine learning models can be applied to prevent, detect, and respond to cyber threats.

Course Structure:

Section 1: Statistics & Machine Learning Basics 📊

• Lecture 1: Central Tendency (Preview)
• Lecture 2: Measures of Dispersion (Preview)
• Lecture 3: Data Visualization
• Lecture 4: Confusion Matrix, Accuracy, and Kappa

Section 2: Case Studies in Cybersecurity with ML 🔒🤖

• Lecture 5: Introduction to Payment Fraud (Preview)
• Lecture 6: Machine Learning in Payment Fraud
• Lecture 7: "NO CODING"_Machine Learning in Payment Fraud
• Lecture 8: Introduction to Malware
• Lecture 9: Machine Learning in Malware
• Lecture 10: Introduction to Phishing
• Lecture 11: Machine Learning in Phishing
• Lecture 12: Introduction to Intrusion Detection Systems (IDS)
• Lecture 13: Machine Learning in IDS
• Lecture 14: Introduction to Spam
• Lecture 15: Machine Learning in Spam
• Lecture 16: Introduction to Twitter Bot Detector
• Lecture 17: Machine Learning in Twitter Bot Detector
• Lecture 18: Introduction to Malicious SQL Injection
• Lecture 19: Machine Learning in SQL Injection
• Lecture 20: "NO CODE"_Machine Learning in Medical Fraud Detection (Preview)

Course Materials:

• Data.zip - A dataset to practice and apply your machine learning skills in real-world cybersecurity scenarios.

By the end of this course, you'll have a solid understanding of how to leverage Python for machine learning in cybersecurity contexts. You'll be well-versed in interpreting data and applying algorithms to enhance security measures and protect against various forms of attacks. This course is perfect for data scientists, cybersecurity professionals, and anyone interested in the overlap of these two critical fields.

Join us on this journey to secure our digital world with data science! 🌐🔎