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10+ Cigna Interview Questions and Answers

Updated 15 Oct 2024

Q1. Which is the best place you will visit for weekend

Ans.

The best place to visit for the weekend would be a peaceful beach resort with stunning views and relaxing atmosphere.

  • Consider visiting a beach resort for a relaxing weekend getaway

  • Look for a place with beautiful views and peaceful surroundings

  • Check for activities like water sports or spa treatments to enhance your experience

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Q2. What is ai? New technologies useful for image generation

Ans.

AI, or artificial intelligence, is the simulation of human intelligence processes by machines, especially computer systems.

  • AI involves the development of algorithms that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

  • Machine learning is a subset of AI that focuses on the development of algorithms that allow computers to learn from and make predictions or decisions based on d...read more

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Q3. What is your data science experience?

Ans.

I have 5 years of experience in data science, including working on various machine learning projects.

  • 5 years of experience in data science

  • Proficient in machine learning techniques

  • Worked on various projects involving data analysis and modeling

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Q4. What is your shirt brand

Ans.

I prefer to wear casual shirts from various brands like Uniqlo, H&M, and Zara.

  • Uniqlo

  • H&M

  • Zara

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Q5. Favorite programming language?

Ans.

Python is my favorite programming language due to its simplicity, readability, and versatility.

  • Python is known for its clean and readable syntax, making it easy to learn and use.

  • It has a large standard library and many third-party libraries for various applications.

  • Python is versatile and can be used for web development, data analysis, artificial intelligence, and more.

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Q6. What is Support vector machine?

Ans.

Support vector machine is a supervised machine learning algorithm used for classification and regression tasks.

  • SVM finds the hyperplane that best separates the classes in the feature space

  • It works well for high-dimensional data and is effective in cases with clear margin of separation

  • Can handle non-linear data by using kernel trick to map data into higher dimensional space

  • Popular kernels include linear, polynomial, radial basis function (RBF)

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Q7. How do you design a database schema for optimal performance?

Ans.

Designing a database schema for optimal performance involves normalization, indexing, partitioning, and denormalization.

  • Normalize the database to reduce redundancy and improve data integrity.

  • Index frequently queried columns to speed up search operations.

  • Partition large tables to distribute data across multiple storage devices for faster access.

  • Consider denormalization for read-heavy applications to reduce join operations.

  • Use appropriate data types and constraints to optimize ...read more

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Q8. Describe your experience with cloud computing platforms.

Ans.

I have extensive experience working with cloud computing platforms such as AWS, Azure, and Google Cloud.

  • Developed and deployed AI models on AWS SageMaker

  • Utilized Azure Machine Learning for model training and deployment

  • Implemented serverless functions on Google Cloud Platform for AI applications

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Q9. Types of ML algorithms

Ans.

ML algorithms are techniques used to enable machines to learn from data and make predictions or decisions without being explicitly programmed.

  • Supervised learning: algorithms learn from labeled training data, e.g. linear regression, support vector machines

  • Unsupervised learning: algorithms find patterns in data without labeled responses, e.g. clustering, dimensionality reduction

  • Reinforcement learning: algorithms learn to make decisions by interacting with an environment, e.g. Q...read more

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Q10. what is the differenece between ml and dl?

Ans.

ML stands for machine learning, while DL stands for deep learning. DL is a subset of ML that uses neural networks to model and solve complex problems.

  • ML (Machine Learning) is a broader concept that involves algorithms and models that can learn from and make predictions or decisions based on data.

  • DL (Deep Learning) is a subset of ML that uses neural networks with multiple layers to model and solve complex problems.

  • DL requires a large amount of data and computational power comp...read more

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Q11. Nave bayes algorithm

Ans.

Naive Bayes algorithm is a probabilistic classifier based on Bayes' theorem with the assumption of independence between features.

  • Naive Bayes is commonly used in text classification, spam filtering, and recommendation systems.

  • It is easy to implement and works well with large datasets.

  • The algorithm assumes that all features are independent of each other, which is a simplifying but often unrealistic assumption.

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