44 Automation Testing courses

This interactive course will help you gain a solid understanding of Protractor. You will get hands-on experience in designing Protractor frameworks for automating Angular applications. You will also understand the role of modern technologies, such as JavaScript, TypeScript, Node.js, and Jasmine, in designing the frameworks.

Advanced Python training course description This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. What will you learn Write Python modules and functions. Evaluate techniques to parse unstructured data. Use NETCONF filters. Handle Python errors effectively (try, assert…). Use postman. Automate testing and validation of the network. Use scrapli, Genie, batfish and Suzieq. Advanced Python training course details Who will benefit: Network engineers. Prerequisites: Python for network engineers Duration 5 days Advanced Python training course contents Review CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli. Hands on: scrapli, Dictionaries versus Regular Expressions. Modules and Functions Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments. Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules. Parsing strategies Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser. Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries. Classes, objects and Python Python classes in Genie, PyEZ and others . Hands on: studying network automation classes, objects, methods and attributes. Configuration management - more nornir, ncclient, requests Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions. Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman. Python error handling and debugging Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt. Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code. Python Automation Testing Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso. Hands on: Using Genie for state comparisons of the network. Network analysis Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest. Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis. Network observability Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes. Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion. Telemetry gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry. Hands on: Analysing telemetry data with Python. Concurrency asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency. Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for software testers, architects, engineers, or other related roles, who wish to apply AI to software testing practices within their enterprise. While there are no specific pre-requisites for this course, it would be helpful is the attendee has familiarity with basic scripting (Python preferred) and be comfortable with working from the command line (for courses that add the optional hands-on labs). Attendees without basic scripting skills can follow along with the hands-on labs or demos. Overview This course introduces AI and related technologies from a practical applied software testing perspective. Through engaging lecture and demonstrations presented by our expert facilitator, students will explore: Exploring AI Introduction to Machine Learning Introduction to Deep Learning Introduction to Data Science Artificial Intelligence (AI) in Software Testing Implementing AI in Test Automation Innovative AI Test Automation Tools for the Future Implementing AI in Software Testing / AI in Test Automation is an introductory-level course for attendees new to AI, Machine Learning or Deep Learning who wish to automate software testing tasks leveraging AI. The course explores the essentials of AI, ML and DL and how the integrate into IT business operations and initiatives. Then the course moves to specifics about the skills, techniques and tools used to apply AI to common software testing requirements. Exploring AI AI-Initiatives The Priority: Excellence AI- Intelligence Types The Machine Learning Types The Quality Learning Initiative The Inception in Academics AI - Importance & Applications The Re-visit Learning Re-visited via AI Teaching in the world of AI Exploring AI for Self-Development AI In Academics Beyond Academics Introduction to Machine Learning What is Machine Learning? Why Machine Learning? Examples - Algorithms behind Machine Learning Introduction to Deep Learning What is Deep Learning? Why Deep Learning? Example - Deep Learning Vs Machine Learning Introduction to Data Science What is Data Science? Why Data Science? Examples - Use Cases of Data Science Artificial Intelligence (AI) in Software Testing What is AI in Software Testing? The Role of AI Testing Why do we Need AI in Software Testing? Pros and Cons of AI in Software Testing Applications of AI in Software Testing Is it time for Testers or QA Teams to worry about AI? Automated Testing with Artificial Intelligence Implementing AI in Test Automation Training the AI Bots Challenges with AI-powered Applications Examples - Real World use cases using Artificial Intelligence Demo - Facial Emotion Detection Using Artificial Intelligence Demo - Text Analysis API Using Artificial Intelligence Demo - EYE SPY Mobile App Using Artificial Intelligence Innovative AI Test Automation Tools for the Future Tools used for Implementing AI in Automation Testing What is NEXT? AI Test Automation Demo using Testim

This course will help you get started with automation testing of web applications. You will cover the basic and advanced topics of Selenium and Python, along with unit tests, pytest, cross-browser testing, logging infrastructure, automation framework design, Jenkins, and a lot more.

Step-by-step tutorial to build a robust automation framework - TestNG, ANT, Maven, Jenkins, Cucumber, Git, Pageobject, Cloud,SQL

This course will help you to get up and running with JMeter. You will learn how to monitor the performance of web applications and REST APIs by load testing, using the features of the JMeter tool.

Advanced Tutorial to Learn essential skills needed to transform your career from QA Engineer to SDET/Test Architect

This course will take you through the basics as well as advanced concepts in TestNG and automation framework building. The course focuses on important concepts such as TestNG, Java, Maven, Selenium WebDriver, page object model, and page factory design. You need to know the basics of core Java and Selenium to get started.

This course is for you if you have no prior coding experience. It is designed to take you through the core Java concepts with the help of practical examples and coding exercises. A course ideal for testing professionals transitioning to DevOps or Automation.

Duration 2 Days 12 CPD hours This course is intended for The target audience for the DevOps Test Engineering course is anyone involved in defining a DevOps Testing strategy, such as: Delivery Staff DevOps Engineers IT Managers Project Managers Lab Staff Maintenance and Support Staff Quality Assurance Managers Quality Assurance Teams Release Managers Testers Software Engineers Overview The learning objectives for DTE include a practical understanding of: The purpose, benefits, concepts and vocabulary of DevOps testing How DevOps testing differs from other types of testing DevOps testing strategies, test management and results analysis Strategies for selecting test tools and implementing test automation Integration of DevOps testing into Continuous Integration and Continuous Delivery workflows How DevOps testers fit with a DevOps culture, organization and roles This comprehensive course addresses testing in a DevOps environment and covers concepts such as the active use of test automation, testing earlier in the development cycle, and instilling testing skills in developers, quality assurance, security, and operational teams. The course is relevant for every modern IT professional involved in defining or deploying a DevOps testing strategy for their organization, as test engineering is the backbone of DevOps and the primary key for successful DevOps pipeline to support digital transformation. This course prepares you for the Continuous Testing Foundation(CTF) certification. Course Objectives and Modules, Logistics What is DevOps Testing and its Business Benefits?Relation of DevOps Testing in other Test MethodologiesDevOps Testing Best Practices DevOps Testing Terminology Culture changes Organization changes Process and team friction Motivation strategies Measuring Success Continuous Evolution Troubleshooting What is the DevOps pipeline? DevOps Testing on the pipeline Test strategy choices Pre-Flight strategies Continuous Integration Testing System, Delivery and Customer Testing Test Environments Lab Management Topology orchestration Test Automation Frameworks Test Tools Selection criterion Automated metrics Key concepts Test Case Best Practices & Design Exercise Test Suite Best Practices & Design Exercise Principles of DevOps Management DevOps Test Management Metrics DevOps Management Tools DevOps Test Results Analysis Integrating DevOps Results Analysis Test Management Exercise Fictitious Product Test Requirements Individual Exercise Class discussion Exam Preparation