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Đề cương khóa học
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)
Phương pháp giảng dạy
Negritu - OMNIASIG VIENNA INSURANCE GROUP S.A.
Course - SoapUI for API Testing
Machine Translated
Tôi rất thích tất cả mọi thứ vì đối với tôi mọi thứ đều mới mẻ và tôi có thể thấy giá trị bổ sung mà nó mang lại cho công việc của mình.
Zareef - BMW South Africa
Course - Tosca: Model-Based Testing for Complex Systems
Machine Translated
Tổng quan rất rộng về nội dung chủ đề đã đi qua tất cả kiến thức tiền đề một cách phù hợp với kiến thức của khóa học.
James Hurburgh - Queensland Police Service
Course - SpecFlow: Implementing BDD for .NET
Machine Translated
Điều đó dễ hiểu và dễ thực hiện.
Thomas Young - Canadian Food Inspection Agency
Course - Robot Framework: Keyword Driven Acceptance Testing
Machine Translated
Số lượng bài tập thực hành.
Jakub Wasikowski - riskmethods sp. z o.o
Course - API Testing with Postman
Machine Translated
