Karate Framework API UI & Performance Testing
** Complete Karate Framework course: API + UI + Performance (Gatling) + AI ** Learn the complete Karate Framework path — REST API automation, browser UI automation, Gatling performance testing, mini projects, and AI-driven Karate implementation. This Karate API, UI and performance testing course is built for manual testers, beginners, and QA engineers who want one complete Karate learning path instead of separate tools. What you will learn in this course: - Karate Framework and Karate DSL fundamentals - REST API automation with powerful assertions and data-driven tests - Karate UI / browser automation for end-to-end flows - Performance testing with Karate and Gatling - Karate API mini project practice (JIRA workflows) - Reusable scenarios and maintainable automation design - AI-driven implementation concepts for Karate - Practical skills for projects and interviews Keywords covered in this course: Karate Framework, Karate DSL, Karate API testing, Karate UI automation, Karate performance testing, Gatling with Karate, REST API automation, end to end automation, API UI performance testing, Karate from scratch, AI for QA. This course combines Karate API, UI, and Gatling performance testing so you can build full-stack Karate automation skills for real projects and interviews. If you are searching for Karate Framework, Karate API UI performance, Karate DSL, or complete Karate automation training in one course, this course is for you. Who this course is for: API testers, API Automation testers, Manual testers
What you'll learn
- Analyze AI workload requirements and select appropriate Azure resources and architectures for modern AI solutions.
- Practice designing Azure AI solutions based on scalability, performance, security, reliability, and operational requirements.
- Evaluate machine learning assets, experiments, training workflows, datasets, and model development strategies.
- Practice working with foundation models, large language models, prompt engineering, embeddings, and retrieval architectures.
- Analyze retrieval-augmented generation scenarios and select appropriate grounding, search, and context strategies.
- Evaluate computer vision, OCR, and intelligent document processing solutions for real-world AI workloads.
- Practice selecting language understanding, speech processing, and conversational AI technologies for different scenarios.
- Analyze retrieval-augmented generation scenarios and select appropriate grounding, search, and context strategies.
- Evaluate computer vision, OCR, and intelligent document processing solutions for real-world AI workloads.
- Practice selecting language understanding, speech processing, and conversational AI technologies for different scenarios.
- Analyze production AI environments involving monitoring, model evaluation, governance, optimization, and continuous improvement.
- Identify appropriate approaches for improving AI model accuracy, performance, scalability, reliability, and operational efficiency.
- Practice making technical AI decisions based on security, responsible AI, governance, cost, and maintainability requirements.
- Strengthen your ability to analyze scenario-based questions covering Azure AI, machine learning, generative AI, vision, language, and operations.
- Prepare for the AI-500 certification exam by mastering Azure AI architecture, machine learning, generative AI, vision, language, and AI operations.
Current deal
Free