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Duration 21 hours
Course Outline
Introduction to AI for QA
- Defining Artificial Intelligence
- Distinguishing between Machine Learning, Deep Learning, and Rule-based Systems
- The transformation of software testing through AI
- Primary advantages and obstacles of implementing AI in QA
Data and ML Basics for Testers
- Differentiating between structured and unstructured data
- Understanding features, labels, and training datasets
- Supervised versus unsupervised learning
- Overview of model evaluation metrics (accuracy, precision, recall, etc.)
- Exploring real-world QA datasets
AI Use Cases in QA
- Generating test cases using AI
- Predicting defects through ML
- Optimizing test prioritization and risk-based testing
- Implementing visual testing via computer vision
- Analyzing logs and detecting anomalies
- Applying NLP to enhance test scripts
AI Tools for QA
- Surveying AI-enabled QA platforms
- Leveraging open-source libraries (e.g., Python, Scikit-learn, TensorFlow, Keras) for QA prototypes
- Integrating LLMs into test automation
- Creating a basic AI model for test failure prediction
Integrating AI into QA Workflows
- Assessing the AI-readiness of current QA processes
- Continuous integration and AI: Embedding intelligence into CI/CD pipelines
- Architecting intelligent test suites
- Handling AI model drift and managing retraining cycles
- Ethical aspects of AI-powered testing
Hands-on Labs and Capstone Project
- Lab 1: Automating test case creation with AI
- Lab 2: Constructing a defect prediction model from historical test data
- Lab 3: Utilizing an LLM to review and refine test scripts
- Capstone: Deploying an end-to-end AI-driven testing pipeline
Requirements
Participants should possess:
- At least 2 years of experience in software testing or QA roles
- Knowledge of test automation tools (e.g., Selenium, JUnit, Cypress)
- Fundamental programming skills (Python or JavaScript preferred)
- Hands-on experience with version control and CI/CD tools (e.g., Git, Jenkins)
- No prior AI/ML background is necessary, although a strong curiosity and readiness to experiment are crucial
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
Key topics can be discussed and agreed upon with the trainer in advance. Relaxed and pleasant atmosphere during the seminar days.
