Talenttrekelearning

Cyber Security

Step Into The Safe Future

This comprehensive course blends foundational cybersecurity principles with essential data science skills.

Students will learn to secure web applications and apply data science techniques such as statistical analysis, data management, machine learning, and data visualization. 

Course Overview

Cybersecurity Introduction
 Understanding cybersecurity threats and vulnerabilities
 Common vulnerabilities (SQL injection, XSS, CSRF)
 Implementing HTTPS and SSL/TLS

Foundations of Data Science
 Overview of the data science workflow
Tools and libraries (Python, Pandas, NumPy, Jupyter Notebooks)

Data Management
SQL vs NoSQL databases
Working with MongoDB and MySQL

 Machine Learning
Supervised vs unsupervised learning
Key algorithms (linear regression, decision trees, clustering)

Visualization Techniques
 Principles of effective visualization
Tools and libraries (Matplotlib, Seaborn, D3.js, Plotly)

Tools Covered

 OWASP ZAP

  Burp Suite

  Wireshark

  Metasploit

  Python, Pandas, NumPy, scikit-learn, TensorFlow

  MongoDB, MySQL

  Matplotlib, Seaborn, D3.js, Platy, Dash

  Git, GitHub, Heroku, Vercel, Netlify, AWS

Projects

Network Intrusion Detection System (NIDS)
Develop a system that monitors network traffic for suspicious activity and potential threats, such as attempted breaches or abnormal traffic flows, using machine learning algorithms.

Skills Developed
Network traffic analysis
Machine learning implementation
Data preprocessing and visualization

Secure File Storage System
Develop a web-based application that allows users to store files securely with end-to-end encryption. Focus on secure upload, storage, and retrieval mechanisms.

Skills Developed:
Encryption and decryption techniques
Web application development
Understanding of cybersecurity principles for data at rest and in transit

Pricing

Sample Certifications

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