LLM Testing Masterclass: Software QA for AI Language Models

About this course

What You'll Learn:

LLM Testing Fundamentals - Master functional and non-functional testing strategies for Large Language ModelsPython AI Testing - Build robust test suites using native Python for machine learning applications

DeepEval Framework - Professional LLM evaluation and testing automation with industry-standard toolsRAG Testing - Test Retrieval Augmented Generation systems with Pinecone vector databases

Hallucination Detection - Identify and prevent AI model hallucinations in production environments

Performance Testing - Optimize LLM response times, accuracy, and reliability

Production AI Testing - Real-world testing strategies for enterprise AI applications

Course Content:

• Neural Network Architecture - Understand LLM foundations and testing requirements

Comprehensive Testing Types - Functional testing (content processing, logical consistency) and non-functional testing (robustness, performance optimization)Python Testing Implementation - Hands-on coding from basic concepts to advanced frameworks

DeepEval Mastery - Professional AI testing automation and continuous integration

Real-World Project - Build and test a complete shoe store RAG application with Pinecone integration

Perfect For:

• AI Developers building LLM-powered applications
• Machine Learning Engineers implementing production AI systemsQA Engineers transitioning to AI testing roles
• Python Developers working with GPT, ChatGPT, and OpenAI APIsData Scientists validating generative AI models
• Software Engineers integrating LLMs into existing applications

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