In today's competitive job market, efficiently extracting key information from resumes is crucial for both job seekers and employers. This project aims to develop a prompt engineering solution using OpenAI's language model to accurately extract education and work history from resumes. The challenge lies in creating a prompt that can handle various resume formats and styles, ensuring consistent and reliable data extraction. The project will involve testing the model's accuracy and speed across a diverse set of example resumes to ensure robustness. By focusing on prompt engineering, learners will apply their understanding of AI models and natural language processing to solve a real-world problem, enhancing their skills in AI application and data extraction.

The project will deliver a well-documented OpenAI model prompt capable of extracting education and work history from resumes with high accuracy. Additionally, a comprehensive report will be provided, detailing the model's performance in terms of accuracy and speed across various resume formats. The report will include insights and recommendations for further improvements, ensuring the solution's applicability in diverse scenarios.