Course Summary
This fundamental course to AI, Artificial Intelligence, gives you a broad insight into the AI methods used to test AI-based solutions and how AI-based solutions can be used to test other IT-systems. Furthermore the following outcome:
• Understand the current state and expected trends of AI
• Experience the implementation and testing of a ML model and recognize where testers can best influence its quality
• Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explain ability
• Contribute to the test strategy for an AI-Based system
• Design and execute test cases for AI-based systems
• Recognize the special requirements for the test infrastructure to support the testing of AI-based systems
• Understand how AI can be used to support software testing
Module 1: Introduction to AI
Module 2: Quality Characteristics for AI-Based Systems
Module 3: Machine Learning (ML)
Module 4: Overview
Module 5: Data
Module 6: Functional Performance Metrics
Module 7: Neural Networks and Testing
Module 8: Testing AI-Based Systems
Module 9: Overview
Module 10: Testing AI-Specific Quality Characteristics
Module 11: Methods and Techniques
Module 12: Test Environments
Module 13: Using AI for Testing
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