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Duration 21 hours
Course Outline
Foundations of AI in QA
- Defining Artificial Intelligence
- Comparing Machine Learning, Deep Learning, and Rule-based Systems
- The trajectory of software testing in the era of AI
- Primary advantages and obstacles of AI in QA
Data and ML Essentials for Testers
- Distinguishing between structured and unstructured data
- Explaining features, labels, and training datasets
- Supervised vs. unsupervised learning approaches
- Basics of model evaluation metrics (accuracy, precision, recall, etc.)
- Examining real-world QA datasets
Practical AI Applications in QA
- Generating test cases with AI
- Predicting defects using ML
- Test prioritization and risk-based testing strategies
- Visual testing leveraging computer vision
- Analyzing logs and detecting anomalies
- Applying NLP to test scripts
AI Toolsets for QA
- Survey of AI-enabled QA platforms
- Developing QA prototypes with open-source libraries (e.g., Python, Scikit-learn, TensorFlow, Keras)
- Introducing LLMs to test automation
- Creating a basic AI model to forecast test failures
Embedding AI into QA Workflows
- Assessing the AI-readiness of your QA processes
- Integrating AI into continuous integration: embedding intelligence into CI/CD pipelines
- Designing intelligent test suites
- Handling AI model drift and retraining schedules
- Ethical implications of AI-powered testing
Practical Labs and Capstone Project
- Lab 1: Automating test case generation 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: Implementing a complete AI-powered testing pipeline
Requirements
Candidates are expected to bring:
- At least two years of experience in software testing or QA positions
- Proficiency with test automation frameworks (e.g., Selenium, JUnit, Cypress)
- Basic programming knowledge (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, provided there is curiosity and a readiness to experiment
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.
