Master the essentials of software quality assurance with our QA manual testing course. Offering flexible learning options, this course is designed for both beginners and professionals seeking to enhance their skills. Whether you’re balancing work or studies, our expert instructors and hands-on approach will prepare you for success in the QA industry. Enrol now and take the first step toward becoming a certified QA manual tester!
In today’s fast-paced software development world, ensuring that products meet quality standards is crucial. Quality Assurance (QA) plays a key role in verifying that applications are working as expected, free from defects, and meet customer requirements. If you’re looking to break into the world of software testing or enhance your skills, a QA manual testing course is your gateway to understanding the intricacies of testing software manually.
This course is specifically designed for beginners and professionals who want to learn manual testing concepts, including test estimations, test planning, test case creation, test execution, and bug reporting. Throughout the course, you will also understand the importance of test techniques, testing types, test management, and generating test summary reports. With these skills in hand, you’ll be well-equipped to handle real-world testing scenarios and contribute to ensuring product quality.
Manual testing is one of the most essential parts of the QA process. Unlike automated testing, manual testing requires testers to check the application from an end-user perspective. Manual testing focuses on identifying bugs, usability issues, and unexpected behaviour that could affect the user experience. Here’s why a QA manual testing course is beneficial:
Manual testing concepts are straightforward, making this course ideal for beginners.
Unlike automated testing, manual testing does not require any programming skills.
Manual testers are always in demand in industries where quality is paramount, especially in sectors like banking, healthcare, and finance.
This QA manual testing course covers a wide array of topics, ensuring you gain an in-depth understanding of how testing works.
Test estimation is one of the core activities in QA manual testing. It involves estimating the time, effort, and resources required for testing. In this course, you will learn different methods of test estimation, such as:
This method divides the test process into small manageable tasks.
It’s a consensus-based estimation method.
A systematic technique for measuring the size of a software project.
Additionally, you’ll understand the importance of creating a test plan. A test plan outlines the scope, objectives, resources, and schedule for the testing process. You will learn how to draft a comprehensive test plan that ensures every aspect of the project is covered. The QA manual testing course will guide you through the different components of a test plan, including:
– Test objectives
– Test deliverables
– Roles and responsibilities
– Risk analysis
– Test schedule
Test cases are the backbone of manual testing. They define the conditions under which a tester will determine whether an application or software system is functioning as expected. In this course, you will be taught how to:
– Write effective test cases that cover both positive and negative scenarios.
– Create test case documentation that is easy to understand and execute.
– Define input data, preconditions, and expected results.
Once test cases are prepared, you will move on to test execution. Test execution is the process of running the test cases on the system under test (SUT) and comparing the actual results with the expected results. The QA manual testing course will teach you to:
– Execute test cases systematically and log the outcomes.
– Identify defects during test execution.
– Collaborate with development teams to resolve issues.
Testing techniques help QA professionals to systematically test an application by breaking down the complexity of software functionalities. As part of this QA manual testing course, you will dive into the following test techniques:
Focuses on testing boundary values for input fields.
Divides input data into equivalent partitions to reduce test cases while maintaining effectiveness.
Helps in testing different combinations of input conditions.
Used to test different system states by providing inputs based on system transitions.
Ensures that the software’s functionality aligns with the requirements.
Focuses on the performance, usability, and security of the application.
Ensures that new code changes do not negatively affect existing functionalities.
A quick check to ensure that the main functions of the application are working after a new build.
These test techniques and testing types are critical to ensuring that you have a well-rounded understanding of manual testing.
One of the most crucial aspects of QA manual testing is identifying and reporting defects. A bug report is a document that outlines the issues found during testing. In this QA manual testing course, you will learn how to create bug reports that include:
– Bug ID
– Severity and Priority
– Steps to Reproduce
– Expected vs Actual Result
– Screenshots or Logs (if applicable)
Proper bug reporting ensures that the development team can quickly identify and resolve issues, improving the overall quality of the application.
After completing the test execution and bug reporting, it’s essential to generate a test summary report. This report summarises the testing activities and provides insights into the test results, such as:
– Number of test cases executed
– Number of passed/failed test cases
– Defects identified and resolved
– Areas of improvement
The QA manual testing course will guide you through creating detailed test summary reports that provide a comprehensive overview of the testing efforts.
Taking a QA manual testing course online offers several advantages:
Learn at your own pace, allowing you to balance work, studies, and personal life.
Study from any location, making it convenient for students and working professionals.
Learn from experienced professionals who provide practical insights and industry-relevant knowledge.
Engage in real-world projects that give you the confidence to apply what you’ve learned in a professional setting.
By the end of this QA manual testing course, you will have a strong foundation in manual testing and will be equipped with the necessary skills to start or advance your career in software testing.
The QA manual testing course is your opportunity to learn the full spectrum of manual testing processes, from planning and test case creation to execution, bug reporting, and test management. This comprehensive course will help you master manual testing techniques that are essential in ensuring software quality, ultimately paving the way for a successful career in QA testing.
Whether you are a beginner or an experienced professional, the knowledge gained from this course will significantly enhance your understanding of manual testing, providing you with the confidence and skills to contribute effectively in the software testing industry.Â
Enrol today and start your journey toward becoming a certified QA manual tester!
Master the essentials of software quality assurance with our Manual Software Testing course. Let’s get into the details of the course and explore how it can enhance your skills in manual software testing.
Course Name | Hours | Duration | Skills & Tools | Eligible Job roles |
---|---|---|---|---|
Manual Software Testing | 50 | 8 Weeks | 1. Various Types of Testing Techniques 2. Test case writing in Excel & TestRail 3. Bug Reporting in Mantis BT & JIRA 4. Manual Testing Projects on multiple domains 5. Agile Methodology | Manual Tester Test Engineer QA Engineer Functional Tester Game Tester |
Don’t miss your chance to join our upcoming batches and start your journey toward becoming a proficient software tester. Secure your spot today! Here is a sneak peek into the upcoming batches:
Course Name | Batch | Timing | Commencement Date | Tentative end Date |
---|---|---|---|---|
Manual Software Testing | Weekdays | 07:00am to 09:00am | 23rd September | [after 8 weeks] |
Manual Software Testing | Weekdays | 07:00pm to 09:00pm | 30th September | [after 8 weeks] |
Manual Software Testing | Weekdays | 10:00am to 01:00pm | 7th October | [after 8 weeks] |
Manual Software Testing | Weekdays | 03:00pm to 06:00pm | 14th October | [after 8 weeks] |
Get to know the expert behind the course—here’s a sneak peek into the trainer’s profile. With years of industry experience and a passion for teaching, our trainer brings practical insights and hands-on expertise to every session.
Head - Learning and Development & Sr. Automation Test Engineer
With a career spanning over 14 years, Shoeb Shaikh has established himself as a dynamic and solutions-driven professional in the fields of software testing, data science, and educational technology. His journey, marked by a series of executive and managerial roles, has honed his skills and shaped him into a leader who thrives on challenges and excels in finding innovative solutions. Currently serving as the Head of Learning & Development at Cinute Digital Private Limited and as a Senior Automation Test Engineer at TESTRIQ QA Lab LLP. His technical expertise, particularly in Agile processes and automation testing frameworks, has driven quality and efficiency in the IT industry. Shoeb’s leadership at Cinute Digital has led to prestigious accreditations, establishing the company as an official ISTQB exam center.
Domain Head - Data Science
Esha Prakash is the Domain Head of Data Science at Cinute Digital Private Limited, dedicated to disseminating Machine Learning (ML) and Business Intelligence (BI) skills. With a strong foundation in data science, Esha has served in various training roles, including at the Bombay Stock Exchange and Imarticus Learning. She has expertise in tools such as Tableau, PowerBI, SQL, Python, and Big Data Analytics. Esha’s contributions extend to content creation, data science consultancy, and mentoring aspiring data scientists. Her certifications in PowerBI, Tableau, and Machine Learning underscore her commitment to continuous learning. Esha has also authored research papers and worked on significant projects in AI and Big Data.
Senior Automation Trainer
Teshoo Rai is a Senior Trainer specializing in Java Automation with Selenium, with over 5 years of experience. Her career focuses on educating professionals in software testing and automation, leading to significant contributions in the field. Teshoo holds a Bachelor of Science in Information Technology and has served as an Assistant Professor and Corporate Trainer. Her expertise includes Agile testing methodologies, automation frameworks, and quality assurance. Teshoo’s leadership at Cinute Digital and TESTRIQ QA Lab LLP has earned the organizations prestigious accreditations and established them as ISTQB exam centers. She is recognized for her ability to mentor and develop tailored corporate training programs.
Senior QA Engineer
Pooja is an ISTQB-certified tester with over 8 years of experience in software testing, including manual and automation testing. She has served as a Corporate Trainer, providing training on Manual Testing, API Testing, Selenium Automation, and more. Pooja has experience working on various projects across industries like finance, education, real estate, and more, with roles in testing, bug tracking, and documentation. She is currently a Corporate Trainer at Cinute Digital Pvt Ltd and has previously worked as a Software Test Engineer at HDFC Pvt Ltd and Testriq QA Labs. Pooja is proficient in using tools like JIRA, Mantis, TFS, and Trello for bug tracking and has strong skills in testing across multiple platforms, including desktop and mobile applications.
Senior Software Test Engineer
Vaibhav Kakade is a Manual Tester at TESTRIQ QA Lab LLP and a Corporate Trainer with Cinute Digital Private Limited. With a background in teaching and training since 2017, Vaibhav has transitioned into IT training, specializing in Manual Software Testing, DBMS with MySQL, and Java Automation with Selenium. He holds certifications from AAA and ISTQB, and an MBA in Project Management. Vaibhav is also involved in grooming participants, resume building, and interview assistance, playing a crucial role in placement activities. His dedication to teaching and training has made him an integral part of both Testriq and CDPL.
Data Science Trainer
Rehmat Shaikh is a visionary data scientist committed to unlocking the potential of data to drive informed decision-making. Her expertise as a Data Science Trainer at Cinute Digital Private Limited reflects her dedication to empowering learners and enabling them to solve real-world problems using data science techniques.Â
Data Science Trainer
Khan Cezzane is a Dynamic Data Science Trainer, with a Bachelor’s in Artificial Intelligence & Data Science Engineering. Cezzane has experience as a Data Analyst and Data Manager, and has worked on impactful projects, including developing a CV and machine learning system for the hearing-impaired. He is dedicated to empowering others through data science education and solving real-world problems.
Cinute Digital stands out due to our unique partnership with Testriq, a leading independent software testing company. This collaboration allows us to offer:
Curriculum infused with real-world industry experience
Practical exercises that mirror actual testing scenarios
Expert mentors with current industry insights
Up-to-date skills aligned with what top companies need
Strong industry connections for internships and job placements
Moreover, we offer a comprehensive learning experience with hands-on projects, certifications, and a guaranteed paid internship, ensuring you're truly job-ready upon completion.
To become an API tester, you can follow these steps:
By following these steps and continuously improving your skills and knowledge, you can become a proficient API tester ready to tackle the challenges of testing modern software applications.
Learning database management systems (DBMS) can be an enriching journey, and here's a step-by-step guide to get started:
Becoming an expert in manual testing requires dedication, continuous learning, and practical experience. Here are steps to help you on your journey:
By following these steps and consistently striving for excellence, you can become an expert in manual testing and make significant contributions to the quality and success of software projects.
Determining the "best" type of automation testing depends on various factors such as project requirements, technology stack, team expertise, and budget constraints. Different types of automation testing have their strengths and are suitable for different scenarios. Here are some popular types of automation testing and their respective advantages:
Ultimately, the "best" type of automation testing depends on the specific goals and requirements of your project. It's essential to consider factors such as the type of application, testing objectives, available resources, and the expertise of your team when selecting the appropriate type of automation testing. In many cases, a combination of different types of automation testing may be necessary to achieve comprehensive test coverage and ensure the quality and reliability of the software.
Determining the "best" institute for manual testing depends on various factors such as your location, budget, preferred mode of learning (online or offline), curriculum quality, faculty expertise, industry reputation, and alumni feedback. Here are some considerations to help you find the right institute for manual testing:
Some reputable institutes for manual testing include:
Ultimately, choose an institute that best fits your learning goals, budget, and career aspirations. It's also beneficial to network with professionals in the industry and seek their recommendations for reputable training programs.
The maximum salary for an automation tester in India can vary depending on several factors including experience, skills, location, company size, industry, and educational background. However, experienced automation testers with advanced skills and expertise can command high salaries in the Indian job market.
As of my last update in January 2022, the maximum salary for an automation tester in India could range anywhere from ₹10 lakhs to ₹30 lakhs per annum or even higher in some cases, particularly for professionals with extensive experience, leadership roles, or specialized skills in high-demand technologies such as Selenium, Appium, or API testing.
It's important to note that salary figures may differ based on the city or region. For instance, metropolitan cities like Bangalore, Hyderabad, Pune, and Chennai often offer higher salaries compared to other cities due to the presence of a thriving IT industry and increased demand for skilled professionals.
Moreover, factors such as certifications (e.g., ISTQB, CSTE, CSQA), additional skills in programming languages (e.g., Java, Python), experience with specific automation tools and frameworks, and domain knowledge (e.g., finance, healthcare, e-commerce) can also influence salary levels.
To get a more accurate estimate of the maximum salary for automation testers in India, it's recommended to research recent job listings, consult salary surveys specific to the IT industry, and consider factors such as market demand and economic conditions at the time of your job search. Additionally, networking with professionals in the field and leveraging online resources can provide valuable insights into salary trends and negotiation strategies.
Comparing the fields of AI (Artificial Intelligence), ML (Machine Learning), and data science is akin to comparing apples, oranges, and bananas—they're related but serve different purposes and have distinct areas of focus. However, each field contributes to advancing technology and solving complex problems in unique ways. Here's a breakdown of each:
So, which is better—AI, ML, or data science? It's not a matter of one being better than the other but rather about understanding their roles and how they complement each other:
Data Science is concerned with extracting insights and knowledge from data, often using statistical methods and tools. It encompasses a broader range of techniques beyond machine learning, including data mining, data cleaning, and data visualization.
Machine Learning is a subset of AI that focuses specifically on developing algorithms and models that enable computers to learn from data. It's a crucial tool in the data scientist's toolkit for building predictive models and making sense of complex datasets.
Artificial Intelligence is the overarching field that encompasses both data science and machine learning, as well as other techniques and methodologies aimed at replicating human intelligence in machines.
In conclusion, the choice between AI, ML, and data science depends on the problem you're trying to solve and the tools and techniques best suited to address that problem. Each field has its own strengths and applications, and practitioners often draw from all three to tackle complex challenges and drive innovation in technology and beyond.
Machine learning is a subset of artificial intelligence (AI) that focuses on developing algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed to do so. In essence, it's about creating systems that can automatically learn and improve from experience.
At its core, machine learning involves feeding data into algorithms to allow them to recognize patterns, make predictions, or generate insights. These algorithms are trained using large datasets, where they learn to identify correlations, trends, and relationships within the data. Through a process of iteration and adjustment, the algorithms improve their performance over time, becoming more accurate and effective at the tasks they're designed for.
There are several types of machine learning approaches, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning, each suited for different types of tasks and data. Supervised learning involves training algorithms on labeled data, where the correct answers are provided alongside the input data. Unsupervised learning, on the other hand, involves training algorithms on unlabeled data, allowing them to discover hidden patterns or structures within the data. Semi-supervised learning combines elements of both supervised and unsupervised learning, while reinforcement learning involves training algorithms to make sequences of decisions through trial and error, with the goal of maximizing cumulative rewards.
Overall, machine learning has become increasingly important in various fields, from finance and healthcare to marketing and cybersecurity, revolutionizing how businesses and organizations leverage data to make informed decisions and automate processes.