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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)
The exercises we saw in the course were quite useful and applicable to my activities at work. Doubts were resolved, and the examples shared are quite helpful.
jocelin salas - BANXICO
Course - Test Automation with Selenium and Python
Machine Translated
The Dynamics.
Cesar Ortiz Lara - Bienes Programados SA de CV
Course - Selenium WebDriver in C#
Machine Translated
Amount of hands-on excersises.
Jakub Wasikowski - riskmethods sp. z o.o
Course - API Testing with Postman
The trainer explained every functionality thoroughly.
Argean Quilaquil - DXC
Course - TestComplete
Trainer is nice. His explanation is clear and interesting. He try to make the lessons interesting as possible. I enjoyed the lesson and gained a lot of knowledge. Thank you so much. The most useful technique I learned is the locating elements for different web component like textbox, radio buttons and buttons. Sometimes, the element ID is not capture correctly. We learned a different way of locating elements by using CSS selectors, XPath, Name and ID. I like the explanation. Thanks
