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1. What is Data Science?

A) The study of database structures

B) The field of analyzing and interpreting complex data

C) The process of data entry

D) A type of software development

Answer: B) The field of analyzing and interpreting complex data

2. Which of the following is NOT a key component of Data Science?

A) Machine Learning

B) Statistics

C) Cloud Computing

D) Data Visualization

Answer: C) Cloud Computing

3. Which programming language is most commonly used in Data Science?

A) Java

B) Python

C) C++

D) PHP

Answer: B) Python

4. What is the main goal of Data Science?

A) To store data efficiently

B) To create beautiful visualizations

C) To extract insights and knowledge from data

D) To build databases

Answer: C) To extract insights and knowledge from data

5. Which library is commonly used for data manipulation in Python?

A) Matplotlib

B) NumPy

C) Pandas

D) TensorFlow

Answer: C) Pandas

6. What is Machine Learning?

A) A method for manual data processing

B) A subset of AI that enables computers to learn from data

C) A type of cloud computing

D) A way to store large datasets

Answer: B) A subset of AI that enables computers to learn from data

7. Which of the following is an example of supervised learning?

A) K-Means Clustering

B) Neural Networks

C) Decision Trees

D) DBSCAN

Answer: C) Decision Trees

8. What does “Big Data” refer to?

A) Data that is stored on a big server

B) Data that cannot be analyzed

C) Extremely large and complex datasets

D) Only structured data

Answer: C) Extremely large and complex datasets

9. Which type of analytics predicts future trends based on past data?

A) Descriptive Analytics

B) Diagnostic Analytics

C) Predictive Analytics

D) Prescriptive Analytics

Answer: C) Predictive Analytics

10. What is the role of a Data Scientist?

A) To clean data only

B) To develop websites

C) To analyze and interpret complex data

D) To manage databases

Answer: C) To analyze and interpret complex data

11. What is a Data Pipeline?

A) A way to store data

B) A system for moving data from one place to another

C) A cloud computing method

D) A data visualization tool

Answer: B) A system for moving data from one place to another

12. Which Python library is commonly used for data visualization?

A) TensorFlow

B) Pandas

C) Matplotlib

D) Scikit-Learn

Answer: C) Matplotlib

13. What is an outlier in a dataset?

A) A data point that is significantly different from other observations

B) A missing value

C) A duplicate entry

D) A well-organized dataset

Answer: A) A data point that is significantly different from other observations

14. What is the first step in Data Science?

A) Data Cleaning

B) Data Collection

C) Data Visualization

D) Model Training

Answer: B) Data Collection

15. Which technique is used for reducing dimensionality in datasets?

A) Regression Analysis

B) Principal Component Analysis (PCA)

C) Decision Trees

D) K-Means Clustering

Answer: B) Principal Component Analysis (PCA)

A) The process of selecting and transforming variables to improve a model

B) The process of creating a dashboard

C) The process of storing data

D) A method for cleaning data

Answer: A) The process of selecting and transforming variables to improve a model

17. What is Deep Learning?

A) A type of reinforcement learning

B) A subset of machine learning that uses neural networks

C) A method for storing data in databases

D) A way to clean unstructured data

Answer: B) A subset of machine learning that uses neural networks

18. Which algorithm is used in recommendation systems?

A) Linear Regression

B) K-Means Clustering

C) Collaborative Filtering

D) Decision Trees

Answer: C) Collaborative Filtering

19. What is Natural Language Processing (NLP)?

A) A technique to process numbers in large datasets

B) The analysis of human language using computers

C) A data storage method

D) A machine learning model

Answer: B) The analysis of human language using computers

20. What does ETL stand for?

A) Extract, Transform, Load

B) Evaluate, Train, Learn

C) Extract, Transfer, Load

D) Encrypt, Transform, Load

Answer: A) Extract, Transform, Load

21. What is a Data Lake?

A) A storage repository that holds vast amounts of raw data

B) A structured database

C) A data visualization tool

D) A cloud computing platform

Answer: A) A storage repository that holds vast amounts of raw data

22. What is Data Wrangling?

A) The process of cleaning and organizing raw data

B) A type of data visualization

C) A way to delete duplicate records

D) A method for creating machine learning models

Answer: A) The process of cleaning and organizing raw data

23. What does SQL stand for?

A) Structured Query Language

B) Statistical Query Language

C) System Query Logic

D) Simple Query Language

Answer: A) Structured Query Language

24. Which algorithm is best suited for classifying emails as spam or not spam?

A) K-Means Clustering

B) Logistic Regression

C) PCA

D) DBSCAN

Answer: B) Logistic Regression

25. What is the purpose of a Confusion Matrix in machine learning?

A) To visualize model performance

B) To create data pipelines

C) To analyze SQL queries

D) To optimize databases

Answer: A) To visualize model performance

26. What does “overfitting” mean in Machine Learning?

A) The model performs well on training data but poorly on new data

B) The model is too simple

C) The model is not trained enough

D) The dataset is too small

Answer: A) The model performs well on training data but poorly on new data

27. Which of the following is an example of unsupervised learning?

A) Linear Regression

B) Logistic Regression

C) K-Means Clustering

D) Decision Trees

Answer: C) K-Means Clustering

28. What is Time Series Analysis used for?

A) Predicting trends over time

B) Analyzing structured data

C) Cleaning datasets

D) Creating dashboards

Answer: A) Predicting trends over time

29. What is Apache Hadoop used for?

A) Storing and processing large datasets

B) Creating dashboards

C) Building neural networks

D) Writing SQL queries

Answer: A) Storing and processing large datasets

30. What is Sentiment Analysis?

A) Analyzing customer emotions from text data

B) Measuring database performance

C) A type of regression analysis

D) A way to reduce storage costs

Answer: A) Analyzing customer emotions from text data

31. What is the difference between classification and regression in machine learning?

A) Classification predicts categories, regression predicts continuous values
B) Regression uses text data, classification uses numbers
C) Classification cleans data, and regression stores data
D) There is no difference
Answer: A) Classification predicts categories, regression predicts continuous values

32. What is cross-validation in machine learning?

A) A method to test SQL queries
B) A technique to reduce overfitting by splitting data into training and testing sets multiple times
C) A type of data visualization
D) A data cleaning tool
Answer: B) A technique to reduce overfitting by splitting data into training and testing sets multiple times

33. What is the function of the Scikit-learn library in Python?

A) Creating visualizations
B) Data entry automation
C) Implementing machine learning algorithms
D) Storing data in databases
Answer: C) Implementing machine learning algorithms

34. What is the “target variable” in supervised learning?

A) The variable used for cleaning
B) The variable that needs to be predicted
C) The variable to be deleted
D) The variable with the most missing data
Answer: B) The variable that needs to be predicted

35. What is the difference between structured and unstructured data?

A) Structured data is organized in rows and columns; unstructured data has no predefined format
B) Structured data is always in images; unstructured data is in tables
C) Unstructured data is easier to store than structured data
D) Structured data is encrypted; unstructured data is not
Answer: A) Structured data is organized in rows and columns; unstructured data has no predefined format

36. Which type of chart is most suitable for comparing categories?

A) Line Chart
B) Bar Chart
C) Histogram
D) Heatmap
Answer: B) Bar Chart

37. What is the “mean” in a dataset?

A) The most frequent value
B) The highest value
C) The average of all values
D) The middle value
Answer: C) The average of all values

38. What is data preprocessing in Data Science?

A) The final step before generating a report
B) The process of preparing raw data for analysis
C) A method for storing large datasets
D) The process of creating machine learning algorithms
Answer: B) The process of preparing raw data for analysis

39. What is a null value in a dataset?

A) A duplicate entry
B) An incorrectly typed entry
C) A missing or undefined value
D) A value with zero
Answer: C) A missing or undefined value

40. What is the role of a Jupyter Notebook in Data Science?

A) To host websites
B) To build mobile applications
C) To write, document, and run code interactively
D) To store data in the cloud
Answer: C) To write, document, and run code interactively

41. What is the purpose of feature scaling in Machine Learning?

A) To delete irrelevant features
B) To normalize data to a standard range for better model performance
C) To increase the number of features
D) To remove missing values
Answer: B) To normalize data to a standard range for better model performance

42. What does the term “bias” mean in a machine learning model?

A) The model performs perfectly on test data
B) Error due to overly simplistic assumptions in the model
C) The model is too complex
D) All values are missing
Answer: B) Error due to overly simplistic assumptions in the model

43. What is the purpose of using Seaborn in Python?

A) File compression
B) Creating advanced and attractive statistical visualizations
C) Reading CSV files
D) Data cleaning
Answer: B) Creating advanced and attractive statistical visualizations

44. What is the full form of CSV in data storage?

A) Column Separated Values
B) Comma-Structured Values
C) Comma-Separated Values
D) Column Structured View
Answer: C) Comma-Separated Values

45. What is the main objective of clustering algorithms?

A) To classify data into fixed labels
B) To group similar data points together
C) To sort data alphabetically
D) To delete null values
Answer: B) To group similar data points together

46. What is the function of the groupby() method in Pandas?

A) To merge multiple DataFrames
B) To split and summarize data based on some criteria
C) To delete duplicate data
D) To visualize bar charts
Answer: B) To split and summarize data based on some criteria

47. What does the head() function do in Pandas?

A) Deletes the first 5 rows
B) Returns the first few rows of a DataFrame
C) Shows summary statistics
D) Plots a histogram
Answer: B) Returns the first few rows of a DataFrame

48. What is the use of the .isnull() function in Pandas?

A) To find duplicate rows
B) To check if a value is greater than a threshold
C) To identify missing values in a DataFrame
D) To convert strings to numbers
Answer: C) To identify missing values in a DataFrame

49. Which chart is suitable to display the correlation between two numeric variables?

A) Pie Chart
B) Line Chart
C) Scatter Plot
D) Area Chart
Answer: C) Scatter Plot

50. What is tokenization in NLP?

A) Converting text into lowercase
B) Removing all numbers from the text
C) Splitting text into individual words or tokens
D) Encrypting the text
Answer: C) Splitting text into individual words or tokens

51. Which of the following is used to handle missing data in a dataset?

A) Clustering
B) Normalization
C) Imputation
D) Tokenization
Answer: C) Imputation

52. Which file format is commonly used to store structured data?

A) .mp4
B) .csv
C) .exe
D) .zip
Answer: B) .csv

53. Which machine learning algorithm is best suited for predicting a continuous value?

A) Logistic Regression
B) Decision Tree
C) K-Means
D) Linear Regression
Answer: D) Linear Regression

54. What is one main benefit of using cloud platforms in Data Science?

A) Data cleaning
B) Cost-free storage
C) Scalability and remote access to data and tools
D) Data entry automation
Answer: C) Scalability and remote access to data and tools

55. In which step of the Data Science process is EDA (Exploratory Data Analysis) performed?

A) After model deployment
B) Before data collection
C) After data collection and cleaning
D) During model training
Answer: C) After data collection and cleaning

56. What is the primary use of the describe() function in Pandas?

A) To rename columns
B) To plot graphs
C) To display summary statistics like mean, median, std
D) To remove null values
Answer: C) To display summary statistics like mean, median, std

57. Which algorithm is an example of a classification technique?

A) K-Means
B) Linear Regression
C) Logistic Regression
D) PCA
Answer: C) Logistic Regression

58. What is the output of a classification model?

A) A continuous number
B) A set of probabilities
C) A category or class label
D) A time series
Answer: C) A category or class label

59. What is one disadvantage of using deep learning models?

A) They require less data
B) They are easy to interpret
C) They are fast with small datasets
D) They need large amounts of data and computing power
Answer: D) They need large amounts of data and computing power

60. What does the value_counts() function in Pandas do?

A) Counts missing values
B) Returns a frequency count of unique values in a column
C) Summarizes numerical columns
D) Splits a DataFrame into groups
Answer: B) Returns a frequency count of unique values in a column

61. Which of the following is a Python IDE used for data science?

A) Dreamweaver
B) PyCharm
C) Notepad++
D) Brackets
Answer: B) PyCharm

62. What does the term ‘training data’ refer to in machine learning?

A) Data used to test the model
B) Data used to monitor model accuracy
C) Data used to build and learn the model
D) Data used for visualization only
Answer: C) Data used to build and learn the model

63. Which command is used to install Python packages?

A) install.packages()
B) pip install
C) conda.create
D) apt-get
Answer: B) pip install

64. Which of the following is NOT a Python data type?

A) List
B) Set
C) Dictionary
D) Table
Answer: D) Table

65. What does a correlation coefficient of -1 indicate?

A) Strong positive relationship
B) No relationship
C) Strong negative relationship
D) Weak relationship
Answer: C) Strong negative relationship

66. Which one is a regression algorithm?

A) Naive Bayes
B) Linear Regression
C) KNN
D) Apriori
Answer: B) Linear Regression

67. What is the default index type in a Pandas DataFrame?

A) Alphabetic
B) Numeric starting from 1
C) Numeric starting from 0
D) UUID
Answer: C) Numeric starting from 0

68. What is the role of the dropna() function in Pandas?

A) To drop duplicate rows
B) To drop rows/columns with missing values
C) To sort the DataFrame
D) To reset the index
Answer: B) To drop rows/columns with missing values

69. Which of the following is a metric for classification models?

A) MSE
B) MAE
C) Accuracy
D) R-squared
Answer: C) Accuracy

70. Which of these libraries is primarily used for scientific computing in Python?

A) Matplotlib
B) NumPy
C) Seaborn
D) Flask
Answer: B) NumPy

71. Which of the following is not a stage of CRISP-DM methodology?

A) Data Understanding
B) Business Understanding
C) Deployment
D) Encryption
Answer: D) Encryption

72. What does API stand for in the context of data science?

A) Automated Python Interface
B) Application Programming Interface
C) Analytics Processing Integration
D) Applied Programming Index
Answer: B) Application Programming Interface

73. Which command is used to display column names in a DataFrame?

A) df.names()
B) df.column_names
C) df.columns
D) df.fields()
Answer: C) df.columns

74. What is one key disadvantage of k-nearest neighbors (KNN)?

A) Difficult to interpret
B) Requires large memory and slow with large data
C) Not used for classification
D) Doesn’t work with numerical data
Answer: B) Requires large memory and slow with large data

75. Which Python function converts a list into a NumPy array?

A) list.array()
B) np.array()
C) pd.array()
D) array.list()
Answer: B) np.array()

76. What is the main difference between Series and DataFrame in Pandas?

A) Series stores strings; DataFrame stores numbers
B) Series is one-dimensional; DataFrame

is two-dimensional
C) Series is for text data only
D) No difference
Answer: B) Series is one-dimensional; DataFrame is two-dimensional

77. Which keyword is used to define a function in Python?

A) def
B) function
C) define
D) fun
Answer: A) def

78. Which of the following is NOT a Python loop structure?

A) for
B) while
C) do-while
D) None of the above
Answer: C) do-while

79. What does the .shape attribute return for a DataFrame?

A) Number of null values
B) List of column names
C) Tuple representing number of rows and columns
D) Data types of each column
Answer: C) Tuple representing number of rows and columns

80. Which of the following is a type of normalization technique?

A) PCA
B) Min-Max Scaling
C) Decision Trees
D) Cross-validation
Answer: B) Min-Max Scaling

81. Which of the following best describes reinforcement learning?

A) Learning from labeled datasets
B) Learning by trial and error with rewards and penalties
C) Learning from clustering algorithms
D) Learning from SQL queries
Answer: B) Learning by trial and error with rewards and penalties

82. What is the purpose of a ROC curve in classification?

A) To visualize database relations
B) To show trade-off between true positive rate and false positive rate
C) To measure regression error
D) To detect missing values
Answer: B) To show trade-off between true positive rate and false positive rate

83. In which scenario is a confusion matrix most useful?

A) Comparing clustering performance
B) Evaluating classification models
C) Measuring regression errors
D) Performing time series forecasting
Answer: B) Evaluating classification models

84. What is “regularization” in machine learning?

A) A method to visualize data
B) A technique to reduce model complexity and prevent overfitting
C) A way to increase dataset size
D) A method for feature encoding
Answer: B) A technique to reduce model complexity and prevent overfitting

85. Which SQL command is used to combine rows from two tables based on a related column?

A) JOIN
B) GROUP BY
C) UNION
D) SELECT DISTINCT
Answer: A) JOIN

86. Which type of learning is used when the algorithm must discover patterns without labeled data?

A) Reinforcement Learning
B) Supervised Learning
C) Unsupervised Learning
D) Semi-Supervised Learning
Answer: C) Unsupervised Learning

87. What is one common method for handling categorical variables in machine learning?

A) Normalization
B) One-Hot Encoding
C) PCA
D) Scaling
Answer: B) One-Hot Encoding

88. Which metric is most commonly used for regression model performance?

A) Accuracy
B) Recall
C) Mean Squared Error (MSE)
D) F1-Score
Answer: C) Mean Squared Error (MSE)

89. Which of the following best describes feature engineering?

A) Writing Python functions
B) Creating new features or modifying existing ones to improve model performance
C) Collecting raw data
D) Storing features in a database
Answer: B) Creating new features or modifying existing ones to improve model performance

90. Which visualization is best for showing distribution of a single continuous variable?

A) Histogram
B) Scatter Plot
C) Bar Chart
D) Heatmap
Answer: A) Histogram