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Course Outline
Module 1: Introduction to AI for QA
- What constitutes Artificial Intelligence?
- Machine Learning versus Deep Learning versus Rule-based Systems
- The evolution of software testing through AI
- Key benefits and challenges of AI in QA
Module 2: Data and ML Basics for Testers
- Understanding structured versus unstructured data
- Features, labels, and training datasets
- Supervised and unsupervised learning
- Introduction to model evaluation (accuracy, precision, recall, etc.)
- Real-world QA datasets
Module 3: AI Use Cases in QA
- AI-driven test case generation
- Defect prediction using ML
- Test prioritisation and risk-based testing
- Visual testing with computer vision
- Log analysis and anomaly detection
- Natural language processing (NLP) for test scripts
Module 4: AI Tools for QA
- Overview of AI-enabled QA platforms
- Utilising open-source libraries (e.g., Python, Scikit-learn, TensorFlow, Keras) for QA prototypes
- Introduction to LLMs in test automation
- Constructing a simple AI model to predict test failures
Module 5: Integrating AI into QA Workflows
- Evaluating the AI-readiness of your QA processes
- Continuous integration and AI: embedding intelligence into CI/CD pipelines
- Designing intelligent test suites
- Managing AI model drift and retraining cycles
- Ethical considerations in AI-powered testing
Module 6: Hands-on Labs and Capstone Project
- Lab 1: Automate test case generation using AI
- Lab 2: Build a defect prediction model using historical test data
- Lab 3: Use an LLM to review and optimise test scripts
- Capstone: End-to-end implementation of an AI-powered testing pipeline
Requirements
Participants are expected to possess:
- Over two years of experience in software testing or QA roles.
- Familiarity with test automation tools (e.g., Selenium, JUnit, Cypress).
- Fundamental knowledge of programming (preferably in Python or JavaScript).
- Experience with version control and CI/CD tools (e.g., Git, Jenkins).
- No prior AI/ML experience is required, though curiosity and a willingness to experiment are essential.
21 Hours
Testimonials (3)
The possibilities of postman and future use of it.
Gordana Gacic - SEE Digital D.O.O.
Course - API Testing with Postman
hands on exercises, easier to retain information
ashley bolen - Insurance Corporation of British Columbia
Course - Test Automation with Selenium
The instructor's teaching style was very good.
