Manual Testing

Manual Testing

Manual testing is a fundamental software testing approach where testers manually execute test cases without the use of any automated testing tools. Testers simulate end-users' interactions with the software to identify defects, ensure its functionality aligns with the requirements, and verify that the application is working as intended.

Skills Covered

SQL. Structured Query Language

Statistical programming. .

Machine learning

Probability and statistics

Data management

Statistical visualization

Advanced Data Analytics Training Course Content Overview

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Skills Covered


Manual testing includes a range of activities that are performed by testers to ensure the quality and functionality of software applications. These activities involve manually executing test cases, interacting with the application, and identifying defects.
manual testing refers to the process of evaluating software applications, systems, or products by manually executing test cases without the use of automation tools or scripts. Manual testing is an essential part of the QA process and involves human testers interacting with the software to identify defects.
Automation testing is a software testing approach that involves using automated testing tools and scripts to execute test cases and verify the functionality of software applications.
Test automation is important across industries for several compelling reasons. It offers numerous benefits that help organizations improve the efficiency, reliability, and quality of their software development and delivery processes.
In order to become an automation test engineer, you will need to have a working knowledge of software development tools, databases, testing tools, and frameworks. You should be able to work as part of a scrum team—following Agile methodologies, building, testing, and delivering features.
A data science course is an educational program designed to teach individuals the skills, tools, and techniques needed to work with and analyze large and complex datasets in order to extract meaningful insights and make informed decisions.
Becoming a data scientist involves a combination of education, skill development, practical experience, and continuous learning.

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