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TechLink Selenium | DevOps | GenAI

Selenium Python Training course videos will help you learn Python, Pytest, WebDriver, and Frameworks. The objective of the course is that you should be able to work on Selenium using Python to an expert level, which can help you clear interviews/work on projects.

We have covered various projects and frameworks, which will give you industry-level experience. On course completion, you will be a master in Selenium Automation Testing with Python and can successfully implement it in your workplace or will surely land High high-paying job

Examples are taken from REAL-

Topics include:

Read more

Selenium Python Training course videos will help you learn Python, Pytest, WebDriver, and Frameworks. The objective of the course is that you should be able to work on Selenium using Python to an expert level, which can help you clear interviews/work on projects.

We have covered various projects and frameworks, which will give you industry-level experience. On course completion, you will be a master in Selenium Automation Testing with Python and can successfully implement it in your workplace or will surely land High high-paying job

Examples are taken from REAL-

Topics include:

  1. Python Basics

  2. Python Modules, Variables, and Data Types

  3. Python Decision-Making & Functions

  4. Python Data Structures and Strings

  5. Python Object-Oriented Programming

  6. Inheritance & its types

  7. Python Encapsulation

  8. Decorators & Generators

  9. Python Exception Handling

  10. Openpyxl and reading Excel files

  11. Writing into an Excel file

  12. What is Pytest | Installing Pytest

  13. Grouping & Parameterizing test cases

  14. Fixtures & Dependency

  15. Pytest Allure Reports

  16. Customizing Allure Report

  17. Project Structure with Python is reusable with any project

  18. What Is Selenium Webdriver? Components of Selenium Webdriver

  19. Downloading Selenium in Eclipse/PyCharm

  20. Launching Browsers with Selenium

  21. Handling Browser Notifications, Proxy Settings, Logs, and SSL Errors

  22. Identification of Objects in Selenium Python WebDriver

  23. Using XPaths with Selenium Python

  24. Using CSS Selectors with Selenium WebDriver

  25. Waiting Strategies, WebElement Features, and Exceptions in Selenium

  26. Multiple Object Extraction

  27. Taking Screenshots, Managing CheckBoxes, Radio Buttons, Dropdowns with Selenium

  28. Multiple Window Handing With Selenium

  29. Managing Frames and Javascript Alerts

  30. Action Class and Performing Complex User Actions

  31. Managing Web tables

  32. Handling Ajax Auto Suggests, JSE & AutoIT

  33. Uploading and Downloading Files With Selenium

  34. Managing Website Cookies

  35. Parallel execution with Selenium Grid

  36. Jenkins and Git Implementation

  37. Data Driven Framework - Happy Testing :)

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What's inside

Learning objectives

  • Zero prior knowledge of webdriver, java & automation testing required. we will start from very basics
  • By the end of the course, you will be able to develop an awesome test automation framework
  • Expertise to become lead sdet / automation architect
  • Last but not least" you can clear any interview and can lead entire selenium automation project from design stage.
  • You will improve your selenium with python coding skills in writing best optimised code for automating test-cases.

Syllabus

Class Variables in Python
Selenium Python Course Introduction
Introduction and Road Map
Start With Selenium Python
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Activities

Coming soon We're preparing activities for Selenium PYTHON : (Basic, Advance, Framework). These are activities you can do either before, during, or after a course.

Career center

Learners who complete Selenium PYTHON : (Basic, Advance, Framework) will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.
This pragmatic guide offers a concise overview of Python's core language features. It's a useful resource for developers who want to quickly grasp the essentials and key concepts of Python without a lengthy introduction.
Great introduction to computer science for beginners. It covers a variety of topics, from algorithms and data structures to object-oriented programming and functional programming.
Is an excellent starting point for beginners who want to learn the basics of Python programming. It covers a wide range of topics, from the fundamentals of the language to more advanced concepts like object-oriented programming and data structures.
Ideal for beginners who want to quickly apply Python to practical tasks. focuses on using Python to automate everyday computer tasks, such as working with files, web scraping, and sending emails. It assumes no prior programming experience and is highly regarded for its clear, step-by-step instructions and focus on immediate productivity gains. The second edition widely used and practical resource.
Uses Python to introduce fundamental computer science concepts. It's a good choice for students or self-learners who want to learn programming within the context of computer science principles. The 3rd edition provides a solid foundation in both Python and computational thinking.
Must-read for anyone who wants to improve their Python programming skills. It covers a variety of advanced topics, from metaprogramming and decorators to generators and coroutines.
Comprehensive reference guide that covers all aspects of the Python language. It great resource for experienced programmers who need to quickly look up information.
Great introduction to data analysis with Python. It covers a variety of topics, from data cleaning and wrangling to data visualization and machine learning.
Great introduction to data analysis for finance with Python. It covers a variety of topics, from data cleaning and wrangling to data visualization and machine learning.
Comprehensive introduction to Python programming. It covers a wide range of topics, from the fundamentals of the language to more advanced concepts like object-oriented programming and data structures.
Is an excellent starting point for anyone new to Python or programming in general. It covers fundamental programming concepts and Python basics with a hands-on, project-based approach, making it very practical for beginners. The third edition is updated to cover newer Python versions and is widely recommended for its clear explanations and engaging projects. It's often used as an introductory textbook.
Is highly recommended for intermediate to advanced Python programmers looking to write more idiomatic and efficient code. It explores Python's often-overlooked features and best practices, delving into topics like data structures, the Python data model, and metaprogramming. It's a valuable resource for deepening understanding and is considered a must-read for those aiming for mastery.
A collection of practical tips and techniques for writing better Python code. focuses on Pythonic practices, lesser-known functionality, and built-in tools to help developers write cleaner, faster, and more robust code. It's suitable for those with a basic understanding of Python who want to improve their coding style and efficiency.
Essential for anyone interested in using Python for data science and analysis. Written by the creator of the pandas library, this book provides comprehensive guidance on manipulating, processing, cleaning, and crunching datasets using pandas, NumPy, and Jupyter. The 3rd edition is updated for recent library versions and standard reference in the data science community.
Offers a collection of tips and tricks to help intermediate Python developers write more professional and Pythonic code. It provides concise explanations and practical examples of various Python features, making it a useful resource for leveling up coding skills and discovering best practices.
While not exclusively a Python book, 'Clean Code' foundational text for any programmer. It teaches principles of writing readable, maintainable, and well-structured code, which are crucial for developing robust applications in Python. provides valuable context and best practices that complement Python-specific knowledge.
A classic computer science textbook that covers fundamental algorithms and data structures. While not Python-specific, understanding these concepts is essential for writing efficient Python programs, especially in technical or academic settings. provides the theoretical foundation necessary for tackling complex problems with Python.
Following up on 'Automate the Boring Stuff,' this book delves into writing cleaner and more maintainable Python code. It covers topics like code formatting, refactoring, and testing, which are essential for building larger and more complex projects.

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