Published 3/2026
Created by Shikhar Verma
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 56 Lectures ( 2h 26m ) | Size: 801 MB
Learn Linux, AWS EC2, Docker & Build AI Apps with Python, GPT-2, Hugging Face & OpenAI Chatbots (Hands-on)
What you’ll learn
✓ Understand the importance of Linux for AI engineering
✓ Launch and manage AWS EC2 (Ubuntu) instances
✓ Connect to virtual machines using tools like MobaXterm
✓ Work confidently with Linux commands, files, and directories
✓ Manage file permissions and ownership (chmod, chown)
✓ Install and manage software using APT package manager
✓ Set up Python environment and virtual environments (venv)
✓ Manage Python dependencies using pip
✓ Run AI models like GPT-2 using PyTorch and Hugging Face
✓ Understand how LLMs and Generative AI work
✓ Use OpenAI and Hugging Face APIs in real projects
✓ Build a complete AI chatbot using Python and OpenAI
✓ Run and test AI applications in a real Linux environment
✓ Containerize applications using Docker (Dockerfile, Image, Container)
✓ Build an AI Chatbot using Python and OpenAI
Requirements
● Basic understanding of computers and internet usage
● No prior Linux knowledge required (we start from basics)
● Basic understanding of Python is helpful but not mandatory
● A laptop or desktop (Windows, Mac, or Linux)
● Internet connection for AWS setup and installations
● Willingness to learn through hands-on practice
● No prior experience in AI, Docker, or cloud is required — everything will be taught step-by-step.
Description
Are you ready to learn Linux for AI engineering and build real-world AI applications from scratch?
In this hands-on course, you will learn how to use Linux, AWS EC2, Python, and Docker to build and deploy AI-powered applications. This course is designed in a step-by-step practical approach, so even beginners can follow along easily.
We will start with Linux basics and gradually move towards AI model execution and chatbot development using modern tools like OpenAI and Hugging Face.
By the end of this course, you will not just understand concepts — you will be able to build, run, and deploy AI applications in a real environment.
What You Will Learn
Getting Started with the Course
• Course Introduction
• Why Linux is Important for AI
• Course Architecture
Getting Started with AWS EC2 & VM Access
• What We Will Cover in This Lecture
• Introduction to Cloud and AWS
• Launch EC2 Instance (Ubuntu)
• Setup MobaXterm for VM Access
• Connecting to VM Using MobaXterm
Linux Fundamentals: Files, Commands & Permissions
• Linux Filesystem Explained
• Learn Essential Linux Commands: pwd, cp, ls & More
• Manage Files in Linux: cat, cp, mv & More
• Editing Files Using the Vi Editor
• File Permissions in Linux
• Modify File Permissions with chmod
• Modifying File Ownership with chown
Package Management & Environment Variables
• Package Management with APT
• Hands-on Lab: Managing Packages with APT
• What are Environment Variables?
• Hands-on Lab: Environment Variables
Python Setup & Dependency Management for AI
• Python Environment Essentials for AI
• Python Virtual Environment Setup (venv)
• Python Dependency Management (pip)
• Real-Time Project: GitHub Info Fetcher – 1
• Real-Time Project: GitHub Info Fetcher – 2
Running AI Models on Linux (GPT-2 Project)
• What We Will Cover
• Install AI Libraries: NumPy, PyTorch & Transformers
• First AI Script: Text Generation
• Loading and Running the GPT-2 Pre-trained Model
• Key Components: Transformers & Hugging Face
• AI Text Generation Flow
• Real-Time Project: AI Text Completion using GPT-2 on AWS
Introduction to Generative AI
• What is an LLM and What Does It Do?
• How LLMs Work?
• Examples of LLM
AI Tools and APIs: OpenAI vs Hugging Face
• API – Application Programming Interface
• OpenAI Introduction: Examples & Use Case
• Hugging Face Overview with Use Cases
• OpenAI vs Hugging Face
Build an AI Chatbot using Python and OpenAI
• AI Chatbot Project Overview
• Setting Up the Python Environment
• Install OpenAI and Other Python Libraries
• Setting Up OpenAI Account and API Key
• Writing Python Code for AI Chatbot
• Running and Testing the AI Chatbot
Deploy the AI Chatbot using Docker
• What is Docker?
• Key Components: Dockerfile, Image, and Container
• What You Will Learn
• Building an AI Chatbot with Docker
• Dockerfile Creation for AI Chatbot
• Writing Python Code for AI Chatbot
• Docker Setup and Installation
• Building a Docker Image using Dockerfile
• Run the AI Chatbot using Docker Container
Why This Course?
• Beginner-friendly, step-by-step approach
• Real-world projects and hands-on labs
• Focus on practical implementation (not just theory)
• Covers complete flow: Linux → AI → Deployment
Final Outcome
By the end of this course, you will be able to
Build, run, and deploy AI applications using Linux, AWS, Docker, and OpenAI.
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