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Build your own AI Resume Checker App using GPT-4, Python, and Streamlit! 🤖 Tired of manually sifting through thousands of resumes? This comprehensive 36-minute tutorial walks you through creating a powerful HR automation tool that scores applicants' resumes against a job description and generates a detailed CSV report. We cover everything from setting up the LlamaIndex framework to integrating the GPT-4 API for advanced, contextual scoring. This application is essential for *HR professionals* looking to streamline the hiring process and *job applicants* who want to use AI to optimize their own resumes against any job post. *Watch next* to master AI app development with Python and LlamaIndex! *** ⏱️ Video Chapters (Timestamps) 0:00 - Course & App Overview (Must start at 0:00) 00:02:20 - The Problem: Why an AI is Needed for Job Application Competition 00:03:52 - Step 1: Installing Required Dependencies (OS, Shutil, Files) 00:04:57 - Setting up the OpenAI API Key and Job Post Folder 00:05:56 - Uploading the Job Post & Folder Creation 00:08:30 - Setting up the AI App and General Job Post Information 00:11:27 - Deep Dive into Code: Importing Libraries and Log Configuration 00014:23 - Understanding LlamaIndex, Vector Index, and Query Engines 00:20:18 - The Main App: Uploading and Processing Applicant Resumes 00:22:37 - Final Input Logic: Comparing Resume to Job Post & GPT-4 Scoring 00:26:47 - Creating the Final CSV Data Frame with Applicant Scores 00:33:34 - Downloading the CSV & Use Cases (Recruiter vs. Applicant) 00:35:43 - Conclusion & Promoting Other AI App Development Courses *** 🛠️ Technology Stack & Tools Used: *Programming Language:* Python *AI Model:* GPT-4 (via OpenAI API) *Frameworks:* Streamlit, LlamaIndex *Libraries:* os, shutils, pip *Goal:* HR Automation, Resume Screening *Don't forget to like, subscribe, and turn on notifications for more free placement and AI app development courses!* #GPT4App #PythonTutorial #Streamlit #LlamaIndex #HRTech #AIResumeChecker #Automation