Teach on Udemy

Turn what you know into an opportunity and reach millions around the world.

Learn More

Your cart is empty.

Keep shopping

Linux Security, AI, Docker And Cloud With Hands-On Labs

Name: Linux Security, AI, Docker And Cloud With Hands-On Labs
Rating: 4.2 (200 reviews)

Learn Linux security, hardening, AI, Docker, cloud, and server protection with practical hands-on labs.

Created byShikhar Verma

Last updated 5/2026

English

English [Auto],

What you'll learn

Understand Linux fundamentals, filesystem structure, and essential Linux commands
Launch and manage Linux servers on AWS EC2 cloud environments
Configure remote VM access using MobaXterm and SSH
Manage Linux file permissions, ownership, and access control securely
Install and manage software packages using APT package manager
Configure environment variables and Python virtual environments for AI workloads
Install and use AI libraries such as NumPy, PyTorch, and Transformers on Linux
Run GPT-2 models and perform AI text generation on Linux systems
Understand LLMs, Generative AI, OpenAI, and Hugging Face concepts
Build AI chatbot applications using Python and OpenAI APIs
Deploy AI applications using Docker containers and Dockerfiles
Understand Linux security fundamentals and server hardening best practices
Configure PAM, password policies, and account security in Linux
Secure Linux servers using SSH hardening, firewall, and SELinux
Implement filesystem security using ACLs and special permissions
Monitor audit logs and apply practical Linux security troubleshooting techniques

Course content

18 sections • 132 lectures • 8h 49m total length

Course Introduction1:53
Why Linux is Important for AI1:26
Course Architecture2:09

What We Will Cover in This Section2:07
Introduction to Cloud and AWS2:27
Explore why cloud computing offers scalable, high performance, accessible servers for AI. Learn AWS EC2 and provisioning a Linux server on the cloud, with local alternatives if needed.
Launch EC2 Instance (Ubuntu)4:21
Setup MobaXterm for VM Access2:12
Connecting to VM Using MobaXterm1:06
Connect to your AWS VM from your local system using MobaXterm by entering the public IP, the Ubuntu user, and the private key in SSH settings to access the server.

Linux Filesystem Explained4:14
Learn Essential Linux Commands: pwd, cp, ls & More6:41
Manage Files in Linux: cat, cp, mv & More5:17
Editing Files Using the Vi Editor2:58
Create and edit files with the vi editor by entering insert mode with i, saving and exiting with escape then colon wq, and viewing content with cat.
File Permissions in Linux4:15
Modify File Permissions with chmod3:23
Learn to change file permissions with chmod using numeric codes: read 4, write 2, execute 1, and set owner, group, and others (7, 6, 0) as shown.
Modifying File Ownership with chown4:06
Learn how to use the chown command to change file ownership, elevating privileges with sudo to switch from Ubuntu to another user, and verify ownership on files such as backup.txt.

Python Environment Essentials for AI3:06
Learn to set up python on ubuntu for ai development, verify python3, install pip, and add libraries like numpy, pandas, and OpenAI via pip; create a virtual environment.
Python Virtual Environment Setup (venv)4:10
Python Dependency Management (pip)4:18
Real-Time Project: GitHub Info Fetcher - 11:33
Real-Time Project: GitHub Info Fetcher - 24:53
Implement a real-time GitHub info fetcher using Python and the requests library, querying the GitHub API for user data in AI-backed cloud back-end contexts.

What We Will Cover1:12
Learn to run ai models on Linux by installing NumPy, PyTorch, and Transformers, explore Hugging Face, and load a real text generation model in a hands-on lab.
Install AI Libraries: NumPy, PyTorch & Transformers3:37
First AI Script: Text Generation3:09
Build your first AI script on Linux using a Python program with Transformers, PyTorch, and NumPy to generate text from user input with a GPT-2 model.
Loading and Running the GPT-2 Pre-trained Model2:38
Key Components: Transformers & Hugging Face1:22
Discover how transformers and Hugging Face enable access to pre-trained models like GPT-2 in code, by loading from Hugging Face and running locally with the transformers library.
AI Text Generation Flow2:25
Real-Time Project: AI Text Completion using GPT-23:40

Introduction to Generative AI2:58
Discover Generative AI, which creates new content by learning from data instead of fixed rules. Generate text, images, audio, and code with tools like ChatGPT and GitHub Copilot.
What is an LLM and What Does It Do?2:40
How LLMs Work?1:23
Trace how an llm works: input a prompt, the model processes text to understand context, predicts the next word, and continues generating to form a final, human-like response in seconds.
Examples of LLM1:05

AI Chatbot Project Overview2:37
Setting Up the Python Environment1:34
Install OpenAI and Other Python Libraries2:17
Install the OpenAI Python library with pip, verify with pip list, and create chatbot.py using vi to initialize the OpenAI client with an API key to enable AI communication.
Setting Up OpenAI Account and API Key1:48
Writing Python Code for AI Chatbot3:50
Write Python code to build an AI chatbot using the OpenAI library, authenticate with an API key, and send user input to the GPT-4o mini model.
Running and Testing the AI Chatbot2:09

What is Docker?1:42
Key Components: Dockerfile, Image, and Container1:32
Explore docker fundamentals with dockerfile, image, and container concepts, including base images, dependencies, and running apps. Learn benefits like consistency, portability, isolation, fast deployment, and production readiness.
What You Will Learn1:29
Building an AI Chatbot with Docker2:53
Dockerfile Creation for AI Chatbot2:08
Writing Python Code for AI Chatbot1:16
Docker Setup and Installation2:53
Building a Docker Image using Dockerfile2:09
Run the AI Chatbot using Docker Container3:07

Requirements

No prior Linux or AI experience is required. This course is designed for beginners as well as intermediate learners.
Basic computer knowledge and familiarity with using a keyboard, browser, and terminal will be helpful.
A Windows, Linux system with internet connectivity is recommended.
Learners should be willing to practice hands-on labs and real-world exercises.
An AWS account (Free Tier is sufficient) is recommended for EC2 cloud-based practice.

Description

This course provides a practical approach to Linux security and hardening while also introducing modern AI and cloud technologies used in real-world environments. You will learn Linux fundamentals, file permissions, package management, environment variables, firewall security, PAM, SELinux, and server protection techniques through hands-on labs and practical demonstrations.

The course also covers AI fundamentals, Python setup for AI workloads, GPT-2 text generation, OpenAI and Hugging Face integration, Docker-based AI application deployment, and cloud-based Linux environments using AWS EC2.

By the end of this course, you will be able to secure Linux systems, work with AI tools on Linux servers, deploy applications using Docker, and build a strong foundation for Linux, DevOps, cloud, AI, and cybersecurity-related roles.

Course Content

Getting Started with the Course

Course Introduction
Why Linux is Important for AI
Course Architecture

Getting Started with AWS EC2 & VM Access

Introduction to Cloud and AWS
Launch EC2 Instance (Ubuntu)
Set Up MobaXterm for VM Access
Connect to VM Using MobaXterm

Linux Fundamentals: Files, Commands & Permissions

Linux Filesystem Explained
Essential Linux Commands
File Management in Linux
Editing Files Using Vi Editor
File Permissions in Linux
Modify Permissions with chmod
Modify Ownership with chown

Package Management & Environment Variables

Package Management with APT
Hands-on Lab: Managing Packages
Environment Variables Explained
Hands-on Lab: Environment Variables

Python Setup & Dependency Management for AI

Python Environment Essentials for AI
Python Virtual Environment Setup (venv)
Python Dependency Management Using pip

Real-Time Projects

GitHub Info Fetcher Project
GitHub API-Based Python Project

Running AI Models on Linux (GPT-2 Project)

Install AI Libraries: NumPy, PyTorch & Transformers
First AI Text Generation Script
Load and Run GPT-2 Model
Transformers & Hugging Face Overview
AI Text Generation Flow

Real-Time Project

AI Text Completion Using GPT-2 on AWS

Introduction to Generative AI

What is an LLM?
How LLMs Work
Examples of LLMs
OpenAI vs Hugging Face
APIs and AI Integrations
OpenAI Introduction & Use Cases
Hugging Face Overview & Use Cases

Build an AI Chatbot Using Python and OpenAI

AI Chatbot Project Overview
Python Environment Setup
Install OpenAI Libraries
Configure OpenAI API Keys
Writing Python Code for AI Chatbot
Run and Test the AI Chatbot

Deploy the AI Chatbot Using Docker

What is Docker?
Docker Architecture & Components
Dockerfile Creation
Docker Setup and Installation
Build Docker Images
Run AI Chatbot Using Docker Containers

Linux Security Fundamentals

Linux Security Overview
Common Linux Security Threats
Server Hardening Best Practices

Linux Security & Hardening

Physical Security of Linux Systems
BIOS Firmware Security
Bootloader Security
Single User Mode Security
PAM (Pluggable Authentication Modules)
Account & Password Security
Password Aging Policies
File System Security
ACLs and Special Permissions
Network Security
SSH Hardening
Linux Firewall & firewalld
Port Forwarding & Rich Rules
SELinux Concepts & Troubleshooting
Audit Logs & Security Monitoring
Last Lecture

Who this course is for:

Beginners who want to learn Linux administration, AI, Docker, cloud, and Linux security from scratch.
Students and IT professionals interested in Linux for AI and cloud environments.
System administrators who want to strengthen their Linux security and hardening skills.
DevOps engineers looking to work with Linux servers, Docker, and cloud-based deployments.
Professionals preparing for Linux, cloud, DevOps, AI, or cybersecurity-related roles.

Linux Security, AI, Docker And Cloud With Hands-On Labs

What you'll learn

Explore related topics

Course content

Getting Started with the Course3 lectures • 5min

Getting Started with AWS EC2 & VM Access5 lectures • 12min

Linux Fundamentals: Files, Commands & Permissions7 lectures • 31min

Package Management & Environment Variables5 lectures • 13min

Python Setup & Dependency Management for AI5 lectures • 18min

Running AI Models on Linux (GPT-2 Project)7 lectures • 18min

Fundamentals of Generative AI and LLMs4 lectures • 8min

AI Tools and APIs: OpenAI vs Hugging Face4 lectures • 6min

Build an AI Chatbot using Python and OpenAI6 lectures • 14min

Deploy the AI Chatbot using Docker9 lectures • 19min

Requirements

Description

Who this course is for: