Build Selenium UI & API Tests in fastest & easiest way using Robot Framework from this Step by step tutorial

Get into Web Development with solid understanding of Angular Basics and write Tests for your code to be White Box tester

This Package help students to onboard into Software Testing Field with all the necessary training on Manual Testing tools/concepts such as (Jira +SQL+Agile+API)

BRAND NEW COURSE - Become expert level Selenium C# Engineer and learn how to implement Automation framework from Scratch

This AI Testing course is designed to be your ideal companion, teaching prompt engineering skills that help you ask the right questions in the right way, enabling you to generate answers swiftly for your everyday testing needs. We will also explore AI-powered testing tools and delve into how QA Automation is evolving with AI intelligence.

This course will introduce you to the World of Machine Learning Models Testing. As AI continues to revolutionize industries, many companies are developing their own ML models to enhance their business operations. However, testing these models presents unique challenges that differ from traditional software testing. Machine Learning Model testing requires a deeper understanding of both data quality and model behavior, as well as the algorithms that power them. This Course starts with explaining the fundamentals of the Artificial Intelligence & Machine Learning concepts and gets deep dive into testing concepts & Strategies for Machine Learning models with real time examples. Please Note:This course highlights specialized testing types and methodologies unique to Machine Learning Testing, with real-world examples. No specific programming language or code is involved in this tutorial.

Welcome to the comprehensive Playwright Python course that covers everything from the basics to frameworks, including Python & Pytest fundamentals without need of any prior Python experience. This course is entirely practical. We will use a fully functional e-commerce application for testing and learn how to automate every scenario of the application, including dynamic components often used in modern React and Angular applications. We will also explore how to perform API testing to create data within the application using Playwright. The course will show you how to conduct end-to-end functional testing, which includes both UI testing and API testing in a single script. This script creates data, tests scenarios, and deletes the data. Advanced topics are discussed, such as grabbing session cookies using APIs and responses to bypass the UI login screen for faster and more reliable execution.

LLMs are everywhere! Every business is building its own custom AI-based RAG-LLMs to improve customer service. But how are engineers testing them? Unlike traditional software testing, AI-based systems need a special methodology for evaluation. This course starts from the ground up, explaining the architecture of how AI systems (LLMs) work behind the scenes. Then, it dives deep into LLM evaluation metrics. This course shows you how to effectively use the RAGAS framework library to evaluate LLM metrics through scripted examples. This allows you to use Pytest assertions to check metric benchmark scores and design a robust LLM Test/evaluation automation framework. What will you learn from the course? High level overview on Large Language Models (LLM) Understand how Custom LLM’s are built using Retrieval Augmented Generation (RAG) Architecture Common Benchmarks/Metrics used in Evaluating RAG based LLM’s Introduction to RAGAS Evaluation framework for evaluating/test LLM’s

Be a Data Quality Assurance Engineer — Build a strong foundation in ETL, Data Warehousing, and testing for data quality. What you will Learn? 1. Understand ETL & Data Warehouse fundamentals with real-world business case examples. 2. Build a complete ETL pipeline using Pentaho Data Integration from scratch. 3. Design effective ETL test scenarios using SQL queries for data quality validation. 4. Understand the scope of ETL testing at each layer of the pipeline with practical examples 5. Learn Slowly Changing Dimensions and how to test them in ETL workflows. 6. Explore ETL vs ELT architectures and when to use each in modern data stacks. 7. Discover why data quality testing is critical before using data to train LLMs and AI models.