Course Description:
This course is designed to introduce beginners to the fundamentals of data science with a focus on applications in IT security. Participants will learn essential data analytics, machine learning, and statistical concepts tailored to cybersecurity contexts, enabling them to analyze security data, detect anomalies, and enhance the protection of digital systems.
Course Objectives:
Understand the basics of data science and its relevance to IT security. Learn foundational data analytics techniques for cybersecurity. Explore machine learning algorithms for anomaly detection and threat analysis. Apply statistical methods to assess security risks and trends. Develop skills in data visualization and interpretation for security insights. Create basic predictive models for cybersecurity applications.
Session 1: Introduction to Data Science in IT Security
Overview of data science and its applications in cybersecurity
Importance of data-driven decision-making in security operations
Session 2: Data Analytics for Security
Data preprocessing and cleaning techniques
Exploratory data analysis for security datasets
Feature engineering for cybersecurity applications
Course Outline :: Data Science for Beginners::
Session 3: Machine Learning for Anomaly Detection
Introduction to machine learning algorithms for anomaly detection
Supervised and unsupervised learning approaches in cybersecurity
Model evaluation and performance metrics.
Session 4: Statistical Analysis in IT Security
Statistical methods for security risk assessment
Probability theory and distributions in cybersecurity
Trend analysis and forecasting using statistical tools.
Session 5: Data Visualization for Security Insights
Importance of data visualization in cybersecurity
Tools and techniques for visualizing security data
Interpretation of visualizations for threat analysis
Session 6: Predictive Modelling in IT Security
Building predictive models for cybersecurity applications
Model deployment and monitoring in security operations.
Ethical considerations in predictive modelling for security
Course Outline :: Data Science for Beginners::
Day 1 Day 2 Day 3
09.00am-10.00am Introduction Session 3 Session 5
10.00am-10.15am Morning tea break Morning tea break Morning tea break
10.15am-12.00pm Session1 Session 3 Session 5
12.00pm- 01.00pm Lunch Lunch Lunch
01.00pm- 03.00pm Session 1 (cont.)
Session 4 Session 6
03.00pm- 03.15pm Afternoon tea break Afternoon tea break Afternoon tea break
03.15pm- 05.00pm Session 2 (cont.) Session 4 Session 6
**The training schedule may change depending on the progress of the class
Programme scope, delivery arrangements and suitability are confirmed during enquiry.