Udemy – AI for QA: Detect Duplicate Test Cases Using AI

Hi there, and welcome to “AI for QA: Detect Duplicate Test Cases Using AI” — a hands-on course where we combine the power of Python, Large Language Models (LLMs) like Gemini, and vector similarity to solve a real-world problem in QA and software testing.

If you’ve ever worked with hundreds of test cases and wondered:

“Am I repeating the same test over and over with slight wording differences?”
then you’re in the right place.

What Are We Building?

In this course, you’re going to build a Python-based utility that reads a CSV file of test cases — and intelligently finds semantically similar or duplicate ones using:

• Text Embeddings from Gemini AI
• Cosine Similarity for vector comparison
• Smart logic to detect similar titles, steps, and expectations

And in the end, you’ll have a tool that can:

• Detect overlapping test cases
• Highlight duplicate coverage
• Help clean up bloated test repositories

What You’ll Learn (Hands-On):

By the end of this course, you’ll be able to:

• Parse raw test case CSV files into structured Python objects
• Use Gemini embeddings to convert titles and actions into semantic vectors
• Apply cosine similarity to detect which test cases are actually “similar in meaning”
• Set thresholds to filter only truly overlapping scenarios
• Export results into JSON or other readable formats

DOWNLOAD LINK: AI for QA: Detect Duplicate Test Cases Using AI

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