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Python + AI for Beginners: Build Your Own Local AI
New
Rating: 5.0 out of 5(1 rating)
6 students

Python + AI for Beginners: Build Your Own Local AI

Learn Python from scratch and build a real AI assistant that runs on your own laptop — no cloud bills, no API keys.
New
Created byGaurav Khurana
Last updated 5/2026
English

What you'll learn

  • Set up a professional Python project with virtual environments, .env files, and .gitignore.
  • Run a Large Language Model on your own laptop with LM Studio — no cloud bill, no API keys
  • Make Python-to-LLM calls using the OpenAI SDK against any OpenAI-compatible endpoint.
  • Build multi-turn chatbots with persistent message history, system prompts, and personas.

Explore related topics

Course content

6 sections • 11 lectures • 2h 45m total length

  • What is Python — install it and run Hello World8:55
  • Install VS Code + Python extension and run your first file7:36
  • Python data types — str, float, boolean, list, dict21:59
  • Python Basics

Requirements

  • No prior programming experience needed — Python basics are taught from zero.
  • A Windows, macOS, or Linux laptop with 8 GB RAM minimum (16 GB recommended) and ~5 GB free disk.
  • Free tools you'll install during the course: Python 3.11+, VS Code, and LM Studio/Ollama. No paid accounts required.

Description

Build a real AI assistant on your own laptop — even if you've never written a line of Python.


This is a hands-on, beginner-first course that takes you from "what is Python?" to shipping a multi-persona AI assistant that runs entirely on your machine using LM Studio. No paid API keys. No credit card. No rate limits while you learn.


What makes this course different

- Local-first - Everything runs on your laptop with free, open-source tools.

- Build, don't watch - Every concept is taught through a Python file you actually run.

- Two files per topic - A short demo file for follow-along and a longer annotated file to study at your own pace.

- Real projects - Three graded assignments and a capstone — all QA-flavored so you finish with a portfolio piece.

- No frameworks until you need them- Pure Python and the OpenAI SDK — that's it.


By the end of this course you'll be able to

- Set up a professional Python project with venv, .env and .gitignore.

- Run a Large Language Model on your own laptop with LM Studio / Ollama.

- Make your first Python → LLM API call.

- Build multi-turn chatbots with memory and system prompts.

- Use the same code with cloud providers like Open Router when you're ready.

- Code 5× faster with GitHub Copilot.

- Ship a menu-driven Personal AI Assistant with multiple personas.


What you'll build

1. Test Case Catalog — a pure-Python data project (Assignment 1).

2. Bug Report Generator — your first real LLM-powered tool (Assignment 2).

3. QA Agent — a multi-skill agent that plans, triages, summarises and assesses risk (Assignment 3).

4. Personal Life Assistant — capstone with multiple AI personas and a menu-driven loop.

5.  Defect Triage Assistant with persistent cross-conversation memory.


Who this course is for

- Absolute beginners who want a friendly entry point to Python and AI in one course.

- Testers, SDETs and QA engineers who want to add AI to their toolkit (assignments are QA-themed).

- Developers from other stacks who want a fast on-ramp to local LLMs.

- Anyone tired of paying for cloud APIs while they learn.


What you DON'T need

- Any prior Python or programming experience.

-  A paid OpenAI / Claude / Gemini account.

-  A high-end GPU (8 GB RAM is enough; 16 GB is comfortable).



Who this course is for:

  • Testers, SDETs, and QA engineers who want to add Python and AI skills to their toolkit.

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