Future Focus Infotech Quality Assurance Analyst Interview Questions and Answers

Q1. Tell me abt your self
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I am a dedicated and hardworking individual with a background in finance and a passion for problem-solving.
• Background in finance

• Strong work ethic

• Passion for problem-solving
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Q1. Salary discussion
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Q1. OOPS concept Java fundamentals
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Q1. Project work framework Rest Assured
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Q1. Self introduction ,,
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I am a dedicated professional with a background in finance and a passion for problem-solving and teamwork.
• Education: Graduated with a degree in Finance from XYZ University, where I was involved in the finance club.

• Experience: Worked as an intern at ABC Corp, where I assisted in financial analysis and reporting.

• Skills: Proficient in Excel and financial modeling, with a strong ability to analyze data and present findings...read more
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Q2. Qalification ,,, information
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Q1. Capital marketing,,,
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Q2. Basic computer knowlege
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It was the easy round to clear they ask basic quans which include DBMS and grammar over all the round was easy

Q1. The test was condected by AI overall the round is easy
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Q1. They asked questions about my project and basic question in java
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AI- boom or a bane was the topic given

Simple programs problems using c++ language

Q1. General discussion on the resume and project work
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Q2. Some HR related questions be confident while answering
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Q1. Swap two numbers without using temp variable
Ans. 
Swap two numbers without using a temp variable
• Use arithmetic operations like addition and subtraction to swap the numbers

• Example: a = 5, b = 10. a = a + b (a = 15), b = a - b (b = 5), a = a - b (a = 10)

• Another example: a = 3, b = 7. a = a + b (a = 10), b = a - b (b = 3), a = a - b (a = 7)
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Q2. What is waterfall model
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Waterfall model is a linear sequential software development process.
• It follows a step-by-step approach where progress flows in one direction, like a waterfall.

• Each phase must be completed before moving on to the next phase.

• Examples of phases in waterfall model: requirements, design, implementation, testing, deployment.
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Q3. Explain about gradient descent algorithm
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Gradient descent is an optimization algorithm used to minimize a function by iteratively moving towards the direction of steepest descent.
• Gradient descent is commonly used in machine learning to optimize the parameters of a model by minimizing the cost function.

• It works by calculating the gradient of the cost function with respect to each parameter and updating the parameters in the opposite direction of the gradient.

• T...read more
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