babymore87
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Build an AI Academic Tutor App with Local Ollama - Zero Cost
Published 8/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 25m | Size: 664 MB
Build a complete AI Academic Tutor with Python, FastAPI, LangChain, Ollama and RAG using local open-source LLMs - FREE
What you'll learn
Build a complete AI Academic Tutor application using Python, FastAPI, LangChain, and local Ollama LLMs.
Run and integrate open-source AI models locally without relying on paid LLM APIs.
Implement RAG to let the AI tutor answer questions using academic documents and study materials.
Connect the AI backend with a user-friendly frontend and turn the components into a working AI application.
Requirements
Basic Python
Basic FastApi
HTML
css
Javascript
Basic langchain
Description
Learn how to build a real AI Academic Tutor application from scratch using local AI models - without paying for LLM APIs.
In this hands-on course, you will build an AI-powered academic tutor that can understand student questions and provide helpful answers using a locally running Large Language Model (LLM).
You will learn how to use Ollama to run open-source AI models on your own computer and connect them to a Python application using FastAPI and LangChain.
You will also learn how to implement Retrieval-Augmented Generation (RAG) so your AI tutor can use academic documents and study materials as a knowledge source when answering questions.
What you will build
By the end of the course, you will have a working AI Academic Tutor application with
A local LLM powered by Ollama
A Python/FastAPI backend
AI-powered question answering
RAG-based document understanding
Academic study material integration
A frontend connected to the AI backend
A complete end-to-end AI application running on your own computer
What makes this course different?
You don't need an OpenAI, Gemini, or other paid LLM API to follow this course. The AI model runs locally on your computer using Ollama, making it an excellent way to learn how modern AI applications work while keeping your development costs at zero.
You will learn by building a real application, rather than only learning AI concepts or making simple API calls.
By the end of the course, you'll understand how the different components of a modern AI application fit together and have a project that you can continue expanding with additional AI features.
Who this course is for
his course is for beginners and developers who want to learn how to build practical AI applications using local LLMs without paying for AI APIs.
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