Data Science Cybersecuity Implementation
Case Studies of Cybersecurity with Machine Learning using Python
Description
Machine learning is disrupting cybersecurity to a greater extent than almost any other industry. Many problems in cyber security are well suited to the application of machine learning as they often involve some form of anomaly detection on very large volumes of data. This course deals the most found issues in cybersecurity such as malware, anomalies detection, SQL injection, credit card fraud, bots, spams and phishing. All these problems are covered in case studies.
Section 1:Statistics - Machine Learning
Lecture 1:Central Tendency (Preview)
Lecture 2:Measures Dispersion (Preview)
Lecture 3:Data Visualization (Preview)
Lecture 4:Confusion Matrix, Accuracy and Kappa
Section 2:Case Studies
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 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)
Data.zip
What You Will Learn!
- Hands-on of Machine Learning in Cybersecurity
- Supervised and unsupervised machine learning models for cybersecurity
Who Should Attend!
- College students
- Those who want a career change