About the course

⭐ Course Description: GenAI Resume Screening System with Databricks (1-Month Program)

Description

This intensive, hands-on course teaches you how to design and build a complete end-to-end Resume Screening System using Generative AI, LLMs, Vector Search, and the Databricks Lakehouse Platform.
You will learn how to ingest, clean, enrich, and transform unstructured resume data using the Medallion architecture, apply large language models for extraction and reasoning, generate text embeddings, perform semantic candidate–job matching, and build an interactive recruiter-facing Databricks App.

This program is designed for developers, data engineers, data scientists, ML engineers, and AI enthusiasts who want to master practical GenAI applications on enterprise-grade infrastructure.

⭐ Key Highlights

• Build a production-grade GenAI Resume Screening System from scratch

• End-to-end implementation using Databricks Lakehouse, Unity Catalog, and Databricks Apps

• Hands-on LLM work: resume parsing, embeddings, semantic search, scoring & ranking, AI summaries

• Real-world Medallion Architecture (Bronze → Silver → Gold)

• Build a fully functional Recruiter AI Assistant with Vector Search + RAG

• Weekly capstone milestones to ensure practical learning

• Enterprise-focused, industry-ready project

⭐ What You Will Learn

1. Generative AI Foundations for Resume Processing

• LLM-based resume parsing (skills, experience, education, job history)

• LLM prompting techniques for structured extraction

• AI-generated candidate summaries and explanations

2. Medallion Architecture for Unstructured Data

• Bronze: ingest PDFs, DOCX, text resumes using Auto Loader

• Silver: extract + normalize text using LLMs

• Gold: embeddings, scoring, and business-model tables

3. Databricks Apps Integration

• Build an interactive Recruiter App

• Semantic candidate search with Vector Index

• Display match scoring, skills mapping, and LLM-generated summaries

• Deploy a fully functional UI without external infrastructure

4. LLM Embeddings & Vector Search

• Generate embeddings for resumes & job descriptions

• Build Databricks Vector Search index

• Semantic similarity & relevance ranking

• Matching candidates to job roles using AI

5. Real-World System Implementation

• Candidate–job matching engine

• Skills & experience scoring logic

• AI-powered decisioning (shortlist/maybe/reject)

• RAG pipeline for recruiter queries

• Full end-to-end deployment workflow

⭐ Who This Course Is For

• Data Engineers

• Data Scientists

• ML/AI Engineers

• Cloud Engineers

• Recruiters/HR Tech Innovators

• Anyone wanting hands-on GenAI + Databricks experience

⭐ By the End of This Course, You Will Be Able To:

• Build GenAI pipelines on Databricks Lakehouse

• Implement Bronze → Silver → Gold workflows for unstructured documents

• Apply LLMs to extract, summarize, and interpret resume data

• Construct scalable vector search & similarity systems

• Create a complete AI-powered resume screening application

• Deliver enterprise-grade GenAI solutions