VW Applied Data Science and Machine Learning for Cybersecurity
Course Description:
Module 1: Introduction to Data Science and Cybersecurity
• Overview of Data Science in Cybersecurity
• Introduction to Cybersecurity Concepts
• Importance of Data-Driven Approaches in Cybersecurity
Module 2: Fundamentals of Data Science
• Data Exploration and Visualization
• Statistical Concepts for Data Analysis
• Data Preprocessing Techniques
Modules 3: Basics of Machine Learning
• Introduction to Machine Learning
• Supervised and unsupervised Learning
• Model Evaluation and Validation
Module 4: Cybersecurity Applications of Machine Learning
• Threat Detection and Analysis
• Anomaly Detection in Network Traffic
• Predictive Analysis for Cyber Threats
Module 5: Practical Implementation and Tools
• Hands-On Projects in Cybersecurity
• Utilizing Machine Learning Libraries (e.g. scikit-learn, TensorFlow)
• Real-world case studies
Module 6: Cybersecurity Defense Strategies
• Proactive Defense Approaches
• Incident Response and Mitigation
• Adaptive Security Measures
Prerequisites
• Basic Programming in Python
• Cybersecurity Basics
• Data Analysis Proficiency
• Machine Learning Basics
For whom is this course?
This hands-on course explores the practical applications of data science and machine learning in cybersecurity, equipping participants with the skills to analyze and defend against cyber threats effectively. The course is designed for cybersecurity professionals, IT specialists, and data enthusiasts seeking to enhance their expertise in leveraging data-driven approaches for proactive and adaptive defense strategies.
What will you Learn?
Practical applications of data science and machine learning in cybersecurity,