Computer Science & IT

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Computer Science & IT MCQ & Objective Questions

Computer Science & IT is a crucial subject for students preparing for school and competitive exams in India. Mastering this field not only enhances your understanding of technology but also significantly boosts your exam scores. Practicing MCQs and objective questions is an effective way to reinforce your knowledge and identify important questions that frequently appear in exams.

What You Will Practise Here

  • Fundamentals of Computer Science
  • Data Structures and Algorithms
  • Operating Systems Concepts
  • Networking Basics and Protocols
  • Database Management Systems
  • Software Engineering Principles
  • Programming Languages Overview

Exam Relevance

Computer Science & IT is an integral part of the curriculum for CBSE, State Boards, and competitive exams like NEET and JEE. Questions often focus on theoretical concepts, practical applications, and problem-solving skills. Common patterns include multiple-choice questions that test your understanding of key concepts, definitions, and the ability to apply knowledge in various scenarios.

Common Mistakes Students Make

  • Confusing similar concepts in data structures, such as arrays and linked lists.
  • Overlooking the importance of algorithms and their time complexities.
  • Misunderstanding the functions and roles of different operating system components.
  • Neglecting to practice coding problems, leading to difficulty in programming questions.
  • Failing to grasp the fundamentals of networking, which can lead to errors in related MCQs.

FAQs

Question: What are the best ways to prepare for Computer Science & IT exams?
Answer: Regular practice of MCQs, understanding key concepts, and reviewing past exam papers are effective strategies.

Question: How can I improve my problem-solving skills in Computer Science?
Answer: Engage in coding exercises, participate in study groups, and tackle a variety of practice questions.

Start your journey towards mastering Computer Science & IT today! Solve our practice MCQs to test your understanding and enhance your exam preparation. Remember, consistent practice is the key to success!

Q. Which evaluation metric is most useful for a model predicting rare events?
  • A. Accuracy
  • B. Recall
  • C. Precision
  • D. F1 Score
Q. Which evaluation metric is NOT typically used for clustering algorithms?
  • A. Silhouette Score
  • B. Davies-Bouldin Index
  • C. Accuracy
  • D. Inertia
Q. Which evaluation metric is NOT typically used for clustering?
  • A. Silhouette Score
  • B. Davies-Bouldin Index
  • C. Adjusted Rand Index
  • D. F1 Score
Q. Which evaluation metric is often used to assess the performance of neural networks in classification tasks?
  • A. Mean Squared Error
  • B. Accuracy
  • C. R-squared
  • D. F1 Score
Q. Which evaluation metric is often used to assess the quality of clustering?
  • A. Accuracy
  • B. Silhouette score
  • C. F1 score
  • D. Mean squared error
Q. Which evaluation metric is particularly useful for ranking predictions?
  • A. Accuracy
  • B. Mean Absolute Error
  • C. Mean Squared Error
  • D. Normalized Discounted Cumulative Gain (NDCG)
Q. Which evaluation metric is used to assess the performance of a recommendation system?
  • A. Root Mean Squared Error
  • B. F1 Score
  • C. Mean Average Precision
  • D. Silhouette Score
Q. Which evaluation metric is used to measure the performance of regression models?
  • A. F1 Score
  • B. Mean Absolute Error
  • C. Confusion Matrix
  • D. ROC Curve
Q. Which feature scaling technique centers the data around zero?
  • A. Min-Max Scaling
  • B. Standardization
  • C. Normalization
  • D. Log Transformation
Q. Which feature transformation technique is used to normalize the range of features?
  • A. One-Hot Encoding
  • B. Min-Max Scaling
  • C. Label Encoding
  • D. Feature Extraction
Q. Which greedy algorithm is used to solve the activity selection problem?
  • A. Dijkstra's algorithm
  • B. Kruskal's algorithm
  • C. Interval scheduling maximization
  • D. Prim's algorithm
Q. Which HTTP method is idempotent and safe?
  • A. POST
  • B. GET
  • C. PUT
  • D. DELETE
Q. Which HTTP method is idempotent, meaning it can be called multiple times without different outcomes?
  • A. POST
  • B. GET
  • C. PUT
  • D. DELETE
Q. Which HTTP method is used to request data from a server?
  • A. POST
  • B. GET
  • C. PUT
  • D. DELETE
Q. Which HTTP method is used to request data from a specified resource?
  • A. POST
  • B. GET
  • C. PUT
  • D. DELETE
Q. Which HTTP method is used to retrieve data from a server?
  • A. POST
  • B. GET
  • C. PUT
  • D. DELETE
Q. Which HTTP method is used to submit data to be processed to a specified resource?
  • A. GET
  • B. POST
  • C. PUT
  • D. DELETE
Q. Which HTTP status code indicates a successful request?
  • A. 200
  • B. 404
  • C. 500
  • D. 301
Q. Which HTTP status code indicates that a resource has been successfully created?
  • A. 200
  • B. 201
  • C. 204
  • D. 404
Q. Which HTTP status code indicates that a resource was not found?
  • A. 200
  • B. 301
  • C. 404
  • D. 500
Q. Which industry commonly uses Decision Trees for risk assessment?
  • A. Healthcare
  • B. Retail
  • C. Insurance
  • D. Manufacturing
Q. Which IP address class is used for large networks with a significant number of hosts?
  • A. Class A
  • B. Class B
  • C. Class C
  • D. Class D
Q. Which IP address class is used for large networks with many hosts?
  • A. Class A
  • B. Class B
  • C. Class C
  • D. Class D
Q. Which IP address class is used for large networks?
  • A. Class A
  • B. Class B
  • C. Class C
  • D. Class D
Q. Which IP address is reserved for the loopback interface?
  • A. 192.168.1.1
  • B. 127.0.0.1
  • C. 10.0.0.1
  • D. 172.16.0.1
Q. Which kernel function is commonly used in Support Vector Machines?
  • A. Linear kernel
  • B. Polynomial kernel
  • C. Radial basis function (RBF) kernel
  • D. All of the above
Q. Which kernel function is commonly used in SVM for non-linear classification?
  • A. Linear kernel
  • B. Polynomial kernel
  • C. Radial basis function (RBF) kernel
  • D. Sigmoid kernel
Q. Which kernel function is commonly used in SVM to handle non-linear data?
  • A. Linear kernel
  • B. Polynomial kernel
  • C. Radial basis function (RBF) kernel
  • D. Sigmoid kernel
Q. Which kernel is commonly used in SVM for non-linear data?
  • A. Linear kernel
  • B. Polynomial kernel
  • C. Radial Basis Function (RBF) kernel
  • D. Sigmoid kernel
Q. Which layer in a CNN is primarily responsible for feature extraction?
  • A. Pooling layer
  • B. Fully connected layer
  • C. Convolutional layer
  • D. Activation layer
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