What you'll learn
Use LangChain framework to create AI applications
Use OpenAI API in Python Apps
Get transcript from YouTube video in Python
Create Web Applications in Python using Streamlits
Requirements
Basic programming concepts
Description
In this course, you will begin by setting up your Python and VS Code development environment. We will then introduce the LangChain Framework, which is a powerful tool for building AI applications. You will also learn about obtaining an OpenAI API Key.Throughout the course, we will guide you in developing a Python application that can read YouTube video transcripts using the pytube library. We will demonstrate how to create a Vector Database from these transcripts using LangChain. Additionally, you will learn how to query the Vector Database using the OpenAI API.Furthermore, we will introduce you to Excalidraw, a versatile tool for creating visual illustrations. App with elegant look and feel will be developed using Python streamlit. Separate lectures are provided on how to install and run strealit apps.Finally, we will guide you in deploying your application using a cloud hosting service, ensuring that it is accessible through a web-based user interface.By the end of this course, you will have gained the necessary skills to build a sophisticated Python app that can process YouTube video transcripts, utilize AI capabilities through the OpenAI API, and present the results through an intuitive web interface.Complete source code will be shared with you on GitHub.
Overview
Section 1: Introduction
Lecture 1 Introduction to the course
Lecture 2 Python Installation
Lecture 3 Install VS Code
Lecture 4 Setup Project Structure in VS Code
Lecture 5 Sketch User Interface in ExcaliDraw
Lecture 6 Create GitHub Repository
Section 2: LangChain and OpenAI
Lecture 7 Introducing Pytube library
Lecture 8 Retrieve YouTube video transcript in Python
Lecture 9 Introduction to LangChain
Lecture 10 How to get OpenAI API Key?
Lecture 11 Create Vector Database from Text File (YouTube Transcript)
Lecture 12 How to Query Vector Database?
Lecture 13 Analyze YouTube Video Transcript
Section 3: Streamlits in Python
Lecture 14 Introduction to Streamlits
Lecture 15 How to install and run streamlits?
Section 4: The Web Interface of Python app using streamlit
Lecture 16 Interface Design
Lecture 17 Developing Final version of the app
Section 5: Publishing the app
Lecture 18 Publish Project on GitHub
Developers who want to develop AI and NLP applications,Organizations who want to use its own data for AI Application,Organizations who want to develop their own ChatGPT like apps



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