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Internship: Resume Parser
Budget: $TBD

Technologies: CSS, HTML, JavaScript

Problem Statement:

Create a solution to parse resumes uploaded in PDF or Word and extract key elements from them. These key elements are typically the structured information found in resumes, such as the applicant's name, contact information, education history, work experience, skills, and other relevant details. The extracted information should be stored in a database.

Key Elements:

File Upload: Allow users to upload resumes in PDF or Word formats. This involves developing a file upload feature in your application.

Document Parsing: Implement a parser that can extract structured information from the uploaded resumes. This may involve using libraries or APIs for document parsing.

Data Extraction: Extract key elements from the resumes, including the applicant's name, contact information, education history, work experience, skills, and any other relevant details.

Database Integration: Store the extracted information in a database for later retrieval and analysis. You will need a database to manage this data.

User Interface: Develop a user-friendly interface that allows users to upload resumes, view parsed information, and interact with the system.

Expected Outcome:

The expected outcome of this project is a functional resume parsing solution that accomplishes the following: Users can upload resumes in PDF or Word format through a user-friendly interface. The system accurately parses and extracts structured information from the uploaded resumes, including but not limited to names, contact details, education history, work experience, and skills. The extracted information is stored in a database for easy retrieval and analysis. Data validation mechanisms ensure that the extracted data is accurate and correctly categorized.

Technologies Used:

To achieve these outcomes, the following technologies may be used:

Front-end Technologies: HTML, CSS, JavaScript for the user interface. Front-end frameworks like React, Angular, or Vue.js may be considered.

Back-end Technologies: A server-side framework or platform (e.g., Node.js, Django, Ruby on Rails) for handling file uploads, parsing, database operations, and user management.

Document Parsing Libraries or APIs: Utilize libraries or APIs that can parse PDF and Word documents. For PDFs, libraries like PDF.js or pdf2json, and for Word documents, libraries like Apache POI or docxtemplater can be used.

Database: Use a database system (e.g., MySQL, PostgreSQL, MongoDB) for storing the extracted information.

Deployment Platforms: Deploy the application on a web server or a cloud platform like AWS, Azure, or Heroku.

Other Considerations:

Data Validation and Cleaning: Develop mechanisms to clean and validate the extracted data to maintain data quality.

Error Handling: Implement error handling to address issues that may arise during the parsing and storage process.