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Course Outline
Module 1: Introduction to AI for QA
- What is Artificial Intelligence?
- Machine Learning vs Deep Learning vs Rule-based Systems
- The evolution of software testing with AI
- Key benefits and challenges of AI in QA
Module 2: Data and ML Basics for Testers
- Understanding structured vs unstructured data
- Features, labels, and training datasets
- Supervised and unsupervised learning
- Intro to model evaluation (accuracy, precision, recall, etc.)
- Real-world QA datasets
Module 3: AI Use Cases in QA
- AI-powered test case generation
- Defect prediction using ML
- Test prioritization 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
- Using open-source libraries (e.g., Python, Scikit-learn, TensorFlow, Keras) for QA prototypes
- Introduction to LLMs in test automation
- Building a simple AI model to predict test failures
Module 5: Integrating AI into QA Workflows
- Evaluating AI-readiness of your QA processes
- Continuous integration and AI: how to embed 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 optimize test scripts
- Capstone: End-to-end implementation of an AI-powered testing pipeline
Requirements
Participants are expected to have:
- 2+ years experience in software testing/QA roles
- Familiarity with test automation tools (e.g., Selenium, JUnit, Cypress)
- Basic 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 required, though curiosity and willingness to experiment are essential
21 Hours
Testimonials (5)
Method of teaching
Negritu - OMNIASIG VIENNA INSURANCE GROUP S.A.
Course - SoapUI for API Testing
I enjoyed everything as it is all new for me and I can see the added value it can ring to my work.
Zareef - BMW South Africa
Course - Tosca: Model-Based Testing for Complex Systems
Very broad overview of the subject matter that ran through all the prerequisite knowledge in ways appropriate to the course knowledge.
James Hurburgh - Queensland Police Service
Course - SpecFlow: Implementing BDD for .NET
It was easy to understand and to implement.
Thomas Young - Canadian Food Inspection Agency
Course - Robot Framework: Keyword Driven Acceptance Testing
Amount of hands-on excersises.
