TCS iON Associate Interview Questions and Answers

Different logical reasoning question over the round

Different dsa question over topics array ,string etc

Q1. Tell me about yourself
Ans. 
I am a dedicated and hardworking individual with a passion for learning and growth.
• I have a Bachelor's degree in Business Administration

• I have 3 years of experience in marketing and sales

• I am proficient in Microsoft Office Suite and social media marketing

• I am a team player and enjoy collaborating with others to achieve goals
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Q2. Tell me your strength
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My strength lies in my ability to effectively communicate and collaborate with team members to achieve common goals.
• Strong communication skills - able to clearly convey ideas and information

• Collaborative nature - work well with others to problem solve and innovate

• Adaptability - able to adjust to changing circumstances and priorities

• Leadership skills - able to motivate and inspire team members towards success
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Q1. Tell me about yourself
Ans. 
I am a dedicated and hardworking individual with a passion for learning and growth.
• I have a strong work ethic and always strive to exceed expectations

• I am a quick learner and adapt well to new environments

• I have experience in project management and team collaboration
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Q2. Tell me your strength
Ans. 
My strength lies in my ability to effectively communicate and collaborate with team members to achieve common goals.
• Strong communication skills

• Collaborative mindset

• Ability to work well in a team

• Problem-solving skills

• Leadership qualities
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Q1. Basic technology
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Some mcq questions and coding question. Both where easy to medium level. Prepare combination/permutation/Time complexity etc

A question related to Binary search and some other follow ups.

Q1. Why did we hired you
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Q2. What is next 5 years see your self
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Q1. Explain random forest
Ans. 
Random forest is an ensemble learning method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting.
• Random forest is a type of ensemble learning method.

• It builds multiple decision trees during training.

• Each tree is built using a subset of the training data and a random subset of features.

• The final prediction is made by averaging the predictions of all the individual trees.

• Random...read more
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Q2. What is boosting
Ans. 
Boosting is a machine learning ensemble technique where multiple weak learners are combined to create a strong learner.
• Boosting is an iterative process where each weak learner is trained based on the errors of the previous learners.

• Examples of boosting algorithms include AdaBoost, Gradient Boosting, and XGBoost.

• Boosting is used to improve the accuracy of models and reduce bias and variance.
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Q1. Reason for switch
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Q2. Job satisfaction
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Q3. Salary negotiation
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Q4. Domain expertise
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Q5. Comfortable for shift timing
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