What you’ll learn
- LLM Testing Fundamentals
- DeepEval Framework
- RAG Testing
- Hallucination Detection
What You’ll Learn:
LLM Testing Fundamentals – Master functional and non-functional testing strategies for Large Language Models
Python AI Testing – Build robust test suites using native Python for machine learning applications
DeepEval Framework – Professional LLM evaluation and testing automation with industry-standard tools
RAG 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 systems
- QA Engineers transitioning to AI testing roles
- Python Developers working with GPT, ChatGPT, and OpenAI APIs
- Data Scientists validating generative AI models
- Software Engineers integrating LLMs into existing applications
Prerequisites:
Basic Python knowledge and familiarity with AI/ML concepts
Why This Course:
Master the critical skills of LLM testing and AI quality assurance that companies desperately need. Learn industry-standard tools like DeepEval, work with cutting-edge technologies like RAG and vector databases, and build portfolio projects that demonstrate real-world AI testing expertise.
Tags: #LLMTesting #AITesting #MachineLearningTesting #PythonAI #DeepEval #RAGTesting #VectorDatabase #Pinecone #AIValidation #MLTesting #GenerativeAI #NLPTesting #AIQualityAssurance #LLMEvaluation #AIAutomation
Who this course is for:
- QA Engineers transitioning to AI testing roles
- AI Developers building LLM-powered applications
- Data Scientists validating generative AI models
- Software Engineers integrating LLMs into existing applications
