> For the complete documentation index, see [llms.txt](https://redi-school-1.gitbook.io/teacher-applicant-hub/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://redi-school-1.gitbook.io/teacher-applicant-hub/tech-and-design-basics/cybersecurity.md).

# Cybersecurity

### 📚 Course Details

* **Schedule:** Tuesday & Thursday, 19:00–21:00 (Online)
* **Format:** Live online lectures with practical exercises. 
* **Final Outcome:** Mini Project & Final project.

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### 👥 Volunteer Roles

* **Session Owner:** Leads classes and introduces new concepts.
* **Session Assistant:** Supports students and manages Zoom logistics during class.
* **Backup Teacher:** Steps in when regular teachers are unavailable.

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### 🧩 Topics Covered

* **IT & Web Fundamentals**
  * Introduction to IT concepts
  * Web technologies overview
  * Systems, architecture, and IT landscape
* **Computer Networks**
  * Networking fundamentals
  * Network protocols and communication
  * Basic network infrastructure
* **Linux for Cybersecurity**
  * Linux fundamentals
  * Command line essentials
  * Introduction to security tools
  * Kali Linux setup and troubleshooting
* **Windows Fundamentals**
  * Windows operating system basics
  * Windows administration
  * Hands-on lab
* **Cybersecurity Fundamentals**
  * Hackers and hacking concepts
  * Cybersecurity principles
  * Common cyber attacks
  * Malware and malware threats
* **Network Security**
  * Network defense concepts
  * Secure communication
  * Introduction to network monitoring
* **Network Scanning & Enumeration**
  * Scanning techniques
  * Enumeration methodologies
  * Network sniffing
  * Hands-on lab with Nmap
* **Defensive Security**
  * Defense in Depth
  * Security controls
  * Basic vulnerability analysis

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### 🎓 Final Project

At the end of the course, students complete a **final project** and give a **presentation** demonstrating their learning.

The project consists of applying a strong foundation, covering supervised learning methods like regression and classification, as well as unsupervised techniques such as clustering and dimensionality reduction.

Take a look at **an example** of what learners will have achieved by the end. 👇

#### <mark style="color:red;">**ON WORK**</mark>

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<h2 align="center"><a href="/pages/0kchzzWzyDzTftgInaI5#volunteer-teacher-recruitment-are-limited-but-more-spots-will-be-reopened-on-thursday-january-8th-at"><mark style="color:orange;background-color:orange;">👋 Book your Meet &#x26; Greet Call!</mark></a></h2>

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Thank you for supporting the ReDI students 🧡

### More info:

* Find out more [About ReDI](/teacher-applicant-hub/about/about-redi-school.md)
* Find out more [About DCP](/teacher-applicant-hub/about/dcp-online.md)
* Find out more [About this Course](https://www.redi-school.org/data-analytics/hamburg/dcp/machine-learning)
* Find out about our [How to Volunteer](/teacher-applicant-hub/about/your-volunteer-journey.md)

### FAQ

* Check out: [I can't teach tonight](broken://pages/wvc6VmyUFvn9NFRtwtJU), [I am dropping out](broken://pages/eUzENWHDhDiXk5y8XwYo), [I feel uncomfortable](broken://pages/yBP7yF6y0QPEZ9r2aK2L).
* In case you have questions, write an email to <dcp-volunteering@redi-schooll.org>.