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Duration 21 hours
Course Outline
Introduction to AI for QA
- The definition of Artificial Intelligence
- Distinguishing between Machine Learning, Deep Learning, and Rule-based Systems
- The transformation of software testing through AI
- Primary advantages and obstacles of integrating AI into QA
Foundations of Data and ML for Testers
- Differentiating between structured and unstructured data
- Understanding features, labels, and training datasets
- Concepts of supervised and unsupervised learning
- Basics of model evaluation metrics (accuracy, precision, recall, etc.)
- Application of real-world QA datasets
AI Applications in QA
- AI-driven test case generation
- Predicting defects using Machine Learning
- Test prioritisation and risk-based testing strategies
- Visual testing techniques employing computer vision
- Log analysis and anomaly detection methods
- Leveraging Natural Language Processing (NLP) for test scripts
AI Toolkits for QA
- Survey of AI-enabled QA platforms
- Utilising open-source libraries (e.g., Python, Scikit-learn, TensorFlow, Keras) for QA prototypes
- Introduction to Large Language Models (LLMs) in test automation
- Developing a basic AI model for predicting test failures
Integrating AI into QA Workflows
- Assessing the AI-readiness of your current QA processes
- Continuous integration and AI: embedding intelligence into CI/CD pipelines
- Designing intelligent and adaptive test suites
- Managing AI model drift and retraining cycles
- Ethical implications of AI-powered testing
Practical Labs and Capstone Project
- Lab 1: Automating test case generation with AI
- Lab 2: Creating a defect prediction model from historical test data
- Lab 3: Utilising an LLM to review and refine test scripts
- Capstone: End-to-end deployment of an AI-driven testing pipeline
Requirements
Candidates are expected to possess the following qualifications:
- At least 2 years of experience in software testing or QA roles
- Proficiency with test automation frameworks (such as Selenium, JUnit, and Cypress)
- Fundamental programming knowledge, ideally in Python or JavaScript
- Hands-on experience with version control and CI/CD platforms (e.g., Git, Jenkins)
- No previous AI/ML background is necessary, although a strong curiosity and readiness to experiment are highly valued
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
Contact us for an exact quote and to hear our latest promotions
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.
