Linux Security, AI, Docker And Cloud With Hands-On Labs
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
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.
Instructor
Shikhar Verma – Entrepreneur, Corporate Trainer, and IT Consultant
●Founder & CEO of Techstart – Leads an IT company specializing in designing, developing certified courses, content creation, and managing online/offline IT projects for renowned companies.
●15+ Years of Industry Experience – Worked extensively in the IT sector before establishing his own business, bringing deep expertise in technology and corporate training.
●Passionate About Technology & Education – Dedicated to utilizing his technical skills to drive both organizational success and personal career growth.
●Renowned Udemy Instructor – Simplifies complex technical concepts and delivers them in an engaging and approachable manner.
●Educating Since 2016 – Taught over 100,000 students worldwide across multiple learning platforms.
●Educational Background – Holds a BTech in Electrical and Electronics Engineering.
●Core Expertise:
☆Generative AI, Python, DevOps, Docker, Git, Kubernetes, Linux, Ansible, Shell Scripting
☁️ AWS Cloud (Amazon Web Services), Linux Clustering, GCP