bita bitaacademy Profile

Selenium with python course
BITA Academy – Your Gateway to Automation Testing Excellence!

Are you ready to take your career in automated testing to the next level? There is no need to look any further! The Selenium with Python course from BITA Academy is your ticket to becoming a skilled automation tester. Join us as we explore the world of Selenium, leverage its power with Python, and get ready for interesting job options. This course will provide you with the information and abilities you need to excel at automation testing.

Course Overview
Our Selenium with Python course is intended to provide you with a thorough understanding of automated testing with Selenium WebDriver and Python. Throughout this course, you will learn how to automate online applications, write strong test scripts, and verify the quality and dependability of your software products.

Introduction to Selenium
Creating a Selenium Environment Using Python
Web Elements Frameworks for Interaction Testing (unittest, pytest)
Handling Alerts and pop-ups
Page Object Model for Data-Driven Testing (POM)
Parallel Testing and Selenium Grid
Best Practices for Real-World Project Work and Advanced Topics
Why use Python with Selenium?
Versatility: Selenium plus Python is a versatile mix for automation testing. Python’s ease of use and readability make it an excellent choice for creating maintainable test scripts.
Robust Ecosystem: Selenium has a large and active community, which ensures constant support and upgrades. Python, as one of the most popular programming languages, offers a diverse set of tools and frameworks to help you improve your testing capabilities.
Career Advancement: Python-skilled Selenium engineers are in high demand in the job market. By completing this course, you will be better prepared to land lucrative jobs in automated testing.
Cross-Browser and Cross-Platform Testing: Selenium allows you to test web applications across several browsers and operating systems, assuring the compatibility of your product.
Selenium with python Curriculum
Syllabus of Selenium with python

Are you ready to take the first step toward excellence in automation testing? Join our Selenium with Python course today and open the door to a world of possibilities!

Opportunities for Selenium with Python Certification
After completing our Selenium with Python course, BITA Academy will certify you. This certification attests to your skill in automated testing and will increase your industry credibility.

Automation Tester: Learn about automated testing and collaborate with leading companies to assure software quality.
Quality Assurance Engineer: Ensure that products fulfill industry standards and customer expectations through quality control.
Selenium Test Automation Engineer: Specialize in Selenium-based automation testing, which is in high demand in the IT business.
QA Analyst: Analyze software and test cases to guarantee seamless and dependable operation.
Test Automation Architect: Design and build strong test automation frameworks for large-scale projects as a Test Automation Architect.

Master Machine Learning course in 50 hrs from Data Scientist. Join Machine Learning Training in Chennai @Bitaacademy and get certified.Best Machine Learning Training in Chennai
BITA Academy – Your Path to Mastering Data Science and AI

With BITA Academy’s Best Machine Learning Training in Chennai, you can unlock the world of data-driven intelligence. Our comprehensive course is designed to provide you with the skills, knowledge, and hands-on experience you need to flourish in the field of Machine Learning and Data Science.

Course Overview
Our Best Machine Learning Training in Chennai is a hands-on curriculum that covers a wide range of topics to ensure you have a thorough understanding of Machine Learning. Here’s a breakdown of what you’ll learn:

Introduction to Machine Learning: Learn about the principles of machine learning, such as supervised and unsupervised learning, regression, and classification.

Data Processing: Learn how to clean, transform, and prepare data for optimal Machine Learning model training.

Feature Engineering: Learn the art of feature selection and engineering in order to improve model performance.

Supervised Learning: Investigate techniques for classification and regression applications such as Decision Trees, Random Forests, and Support Vector Machines.

Unsupervised Learning: Learn about clustering and dimensionality reduction techniques like K-Means and PCA.

Deep Learning: Deep learning uses master neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) to perform complicated tasks such as image recognition and natural language processing.

Model Evaluation and Optimization: Discover how to evaluate model performance, tune hyperparameters, and avoid common traps.

Real-World Projects: Put your knowledge to use by working on real-world projects such as predictive analytics, recommendation systems, and sentiment analysis.