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Question 1/101/10
What is a correct call to the linear search defined as def linear_search(customersList, search_value): ?
A find_linear(customersList)
B print(linear_search(customersList, search_value))
C linear_search()(customersList)
D search_linear(customersList, search_value)
A find_linear(customersList)
B print(linear_search(customersList, search_value))
C linear_search()(customersList)
D search_linear(customersList, search_value)
Check the image below to see the right answer:Select the answer
1 correct answerA function definition in Python specifies a function name and a list of parameters. Here, def
linear_search(customersList, search_value): defines a function named linear_search that requires two
arguments when called: a list (or sequence) of customer items and the value being searched for. A
correct call must therefore supply both arguments in the same order: linear_search(customersList,
search_value).
linear_search(customersList, search_value): defines a function named linear_search that requires two
arguments when called: a list (or sequence) of customer items and the value being searched for. A
correct call must therefore supply both arguments in the same order: linear_search(customersList,
search_value).
Quiz
Question 2/102/10
Which aspect of a security policy would define the ramifications of abusing company resources?
A Network Security Policy
B Physical Security Policy
C Acceptable Use Policy
D Data Retention Policy
A Network Security Policy
B Physical Security Policy
C Acceptable Use Policy
D Data Retention Policy
Check the image below to see the right answer:Select the answer
1 correct answerAn Acceptable Use Policy (AUP)defines how employees and users are permitted to use an
organization’s computing resources—such as email, internet access, file storage, endpoints, and
networks—and it typically specifies prohibited behaviors and the consequences of violations. In security
and IT governance textbooks, the AUP is framed as both a behavioral contract and a risk-management
tool: it reduces misuse, clarifies expectations, and provides an enforceable basis for disciplinary action.
The “ramifications of abusing company resources” (for example, installing unauthorized software,
excessive personal use, accessing inappropriate content, attempting to bypass security controls, or
sharing credentials) are precisely the kinds of issues an AUP addresses. The policy often includes
monitoring statements (users have limited expectation of privacy), compliance requirements, and
escalation paths for violations.
A Network Security Policy (A) focuses on technical rules for network protection—firewalls, segmentation,
remote access, and intrusion detection—rather than broad user conduct and disciplinary consequences.
A Physical Security Policy (B) addresses protection of facilities and hardware—badges, locks, visitor
procedures, secure areas. A Data Retention Policy (D) defines how long data is stored, how it is
archived, and how it is disposed, which is different from defining misuse consequences.
Thus, the policy aspect that defines permissible behavior and the consequences for abusing resources is
the Acceptable Use Policy.
organization’s computing resources—such as email, internet access, file storage, endpoints, and
networks—and it typically specifies prohibited behaviors and the consequences of violations. In security
and IT governance textbooks, the AUP is framed as both a behavioral contract and a risk-management
tool: it reduces misuse, clarifies expectations, and provides an enforceable basis for disciplinary action.
The “ramifications of abusing company resources” (for example, installing unauthorized software,
excessive personal use, accessing inappropriate content, attempting to bypass security controls, or
sharing credentials) are precisely the kinds of issues an AUP addresses. The policy often includes
monitoring statements (users have limited expectation of privacy), compliance requirements, and
escalation paths for violations.
A Network Security Policy (A) focuses on technical rules for network protection—firewalls, segmentation,
remote access, and intrusion detection—rather than broad user conduct and disciplinary consequences.
A Physical Security Policy (B) addresses protection of facilities and hardware—badges, locks, visitor
procedures, secure areas. A Data Retention Policy (D) defines how long data is stored, how it is
archived, and how it is disposed, which is different from defining misuse consequences.
Thus, the policy aspect that defines permissible behavior and the consequences for abusing resources is
the Acceptable Use Policy.
Quiz
Question 3/103/10
What Python code would return the value 40 from np_2d, where np_2d = np.array([[1, 2, 3, 4], [10, 20,
30, 40]])?
A np_2d[3, 1]
B np_2d[1, 3]
C np_2d[0, 4]
D np_2d[4, 1]
30, 40]])?
A np_2d[3, 1]
B np_2d[1, 3]
C np_2d[0, 4]
D np_2d[4, 1]
Check the image below to see the right answer:Select the answer
1 correct answerIn a 2D NumPy array, indexing is written as array[row_index, column_index] using zero-based indices.
The array np_2d = np.array([[1, 2, 3, 4], [10, 20, 30, 40]]) has two rows (indices 0 and 1) and four
columns (indices 0, 1, 2, 3). The value 40 is located in the second row and the fourth column. Using
zero-based indexing, that corresponds to row index 1 and column index 3. Therefore, np_2d[1, 3] returns
40.
Option A attempts to access row 3, which does not exist and would raise an IndexError. Option C
attempts to access column 4 in row 0, but valid column indices are only 0 through 3, so it would also
error. Option D likewise refers to a non-existent row 4. Only option B uses valid indices and points to the
correct location.
Textbooks emphasize multi-dimensional indexing because it underlies matrix operations, dataset
manipulation, and feature extraction in data science. Correctly interpreting rows and columns is essential
when rows represent observations (like people) and columns represent attributes (like age, weight,
height). This question tests precise control over row/column addressing, which prevents subtle bugs in
numerical analysis.
The array np_2d = np.array([[1, 2, 3, 4], [10, 20, 30, 40]]) has two rows (indices 0 and 1) and four
columns (indices 0, 1, 2, 3). The value 40 is located in the second row and the fourth column. Using
zero-based indexing, that corresponds to row index 1 and column index 3. Therefore, np_2d[1, 3] returns
40.
Option A attempts to access row 3, which does not exist and would raise an IndexError. Option C
attempts to access column 4 in row 0, but valid column indices are only 0 through 3, so it would also
error. Option D likewise refers to a non-existent row 4. Only option B uses valid indices and points to the
correct location.
Textbooks emphasize multi-dimensional indexing because it underlies matrix operations, dataset
manipulation, and feature extraction in data science. Correctly interpreting rows and columns is essential
when rows represent observations (like people) and columns represent attributes (like age, weight,
height). This question tests precise control over row/column addressing, which prevents subtle bugs in
numerical analysis.
Quiz
Question 4/104/10
Which action is taken if the first number is the lowest value in a selection sort?
A The first number is increased by one.
B The first number is duplicated.
C It swaps the selected element with the last unsorted element.
D It swaps the selected element with the first unsorted element.
A The first number is increased by one.
B The first number is duplicated.
C It swaps the selected element with the last unsorted element.
D It swaps the selected element with the first unsorted element.
Check the image below to see the right answer:Select the answer
1 correct answerSelection sort works by maintaining a boundary between a sorted prefix and an unsorted suffix. On each
pass, the algorithm finds the smallest value in the unsorted portion and places it into the first position of
that unsorted portion (which is also the next position in the sorted prefix). This is usually done by
swapping the element at the minimum’s index with the element at the boundary index (the “first unsorted
element”). That description matches option D.
If the first element of the unsorted portion is already the smallest, then the minimum’s index equals the
boundary index. In textbook implementations, the algorithm may still execute a swap operation, but it
becomes a swap of an element with itself (a no-op), leaving the array unchanged. Many implementations
include a small optimization: perform the swap only if the minimum index differs from the boundary
index. Either way, conceptually the “action taken” by selection sort is still “swap the selected minimum
into the first unsorted position,” which is exactly what option D states.
Options A and B are unrelated to sorting; selection sort never increases or duplicates values. Option C is
incorrect because selection sort swaps the minimum with thefirstunsorted element, not the last. After the
swap (or no-op), the sorted region grows by one element, and the algorithm repeats from the next
boundary position.
This logic is fundamental for understanding how selection sort ensures correctness: after pass i, the
smallest i+1 elements are fixed in their final positions.
pass, the algorithm finds the smallest value in the unsorted portion and places it into the first position of
that unsorted portion (which is also the next position in the sorted prefix). This is usually done by
swapping the element at the minimum’s index with the element at the boundary index (the “first unsorted
element”). That description matches option D.
If the first element of the unsorted portion is already the smallest, then the minimum’s index equals the
boundary index. In textbook implementations, the algorithm may still execute a swap operation, but it
becomes a swap of an element with itself (a no-op), leaving the array unchanged. Many implementations
include a small optimization: perform the swap only if the minimum index differs from the boundary
index. Either way, conceptually the “action taken” by selection sort is still “swap the selected minimum
into the first unsorted position,” which is exactly what option D states.
Options A and B are unrelated to sorting; selection sort never increases or duplicates values. Option C is
incorrect because selection sort swaps the minimum with thefirstunsorted element, not the last. After the
swap (or no-op), the sorted region grows by one element, and the algorithm repeats from the next
boundary position.
This logic is fundamental for understanding how selection sort ensures correctness: after pass i, the
smallest i+1 elements are fixed in their final positions.
Quiz
Question 5/105/10
What is the alternative way to access the third element of the first row in np_2d?
A np_2d[1, 3]
B np_2d[2, 0]
C np_2d[3, 1]
D np_2d[0, 2]
A np_2d[1, 3]
B np_2d[2, 0]
C np_2d[3, 1]
D np_2d[0, 2]
Check the image below to see the right answer:Select the answer
1 correct answerNumPy arrays use zero-based indexing, meaning counting starts at 0 rather than 1. In a 2D NumPy
array, indexing is typically written in the form array[row_index, column_index]. The first index selects the
row, and the second index selects the column. Therefore, the “first row” corresponds to row index 0.
Within that row, the “third element” corresponds to column index 2, because the columns are indexed 0,
1, 2, 3, and so on.
So, np_2d[0, 2] directly selects the element at row 0 and column 2, which is the third element in the first
row. This is considered an “alternative” to approaches like two-step indexing (np_2d[0][2]), and it is the
standard idiom taught for multi-dimensional NumPy arrays.
The other choices point to different locations. np_2d[1, 3] is the fourth element of the second row, not the
third element of the first row. np_2d[2, 0] and np_2d[3, 1] attempt to access the third or fourth row, which
would often be out of bounds in a small 2-row example and would raise an IndexError. Correct indexing
is a cornerstone of array programming because it determines which observation, feature, or matrix entry
your computations will use.
array, indexing is typically written in the form array[row_index, column_index]. The first index selects the
row, and the second index selects the column. Therefore, the “first row” corresponds to row index 0.
Within that row, the “third element” corresponds to column index 2, because the columns are indexed 0,
1, 2, 3, and so on.
So, np_2d[0, 2] directly selects the element at row 0 and column 2, which is the third element in the first
row. This is considered an “alternative” to approaches like two-step indexing (np_2d[0][2]), and it is the
standard idiom taught for multi-dimensional NumPy arrays.
The other choices point to different locations. np_2d[1, 3] is the fourth element of the second row, not the
third element of the first row. np_2d[2, 0] and np_2d[3, 1] attempt to access the third or fourth row, which
would often be out of bounds in a small 2-row example and would raise an IndexError. Correct indexing
is a cornerstone of array programming because it determines which observation, feature, or matrix entry
your computations will use.
Quiz
Question 6/106/10
How can someone subset the last two rows and columns of a 2D NumPy array?
A array[-2:, :]
B array[-1:, -1:]
C array[-2:, -2:]
D array[:, -2:]
A array[-2:, :]
B array[-1:, -1:]
C array[-2:, -2:]
D array[:, -2:]
Check the image below to see the right answer:Select the answer
1 correct answerNumPy slicing uses the same start/stop rules as Python sequences, and it also supports negative
indices to count from the end. In a 2D array, slicing is written as array[rows, columns]. To get thelast two
rows, you use -2: in the row position, meaning “start two rows from the end and go to the end.” Similarly,
to get thelast two columns, you use -2: in the column position. Combining these gives array[-2:, -2:],
which selects the bottom-right 2×2 subarray.
Option A, array[-2:, :], selects the last two rows butall columns, so it is not restricted to the last two
columns. Option D, array[:, -2:], selects all rows but only the last two columns. Option B, array[-1:, -1:],
selects only the last row and the last column, producing a 1×1 (or 1×1 view) subarray, not a 2×2.
This kind of slicing is widely taught because it is essential for matrix operations, extracting submatrices,
working with sliding windows, and manipulating image or time-series data where “take the last k
observations/features” is common. Negative indexing reduces errors and makes code clearer, especially
compared with computing explicit indices like array[rows-2:rows, cols-2:cols].
indices to count from the end. In a 2D array, slicing is written as array[rows, columns]. To get thelast two
rows, you use -2: in the row position, meaning “start two rows from the end and go to the end.” Similarly,
to get thelast two columns, you use -2: in the column position. Combining these gives array[-2:, -2:],
which selects the bottom-right 2×2 subarray.
Option A, array[-2:, :], selects the last two rows butall columns, so it is not restricted to the last two
columns. Option D, array[:, -2:], selects all rows but only the last two columns. Option B, array[-1:, -1:],
selects only the last row and the last column, producing a 1×1 (or 1×1 view) subarray, not a 2×2.
This kind of slicing is widely taught because it is essential for matrix operations, extracting submatrices,
working with sliding windows, and manipulating image or time-series data where “take the last k
observations/features” is common. Negative indexing reduces errors and makes code clearer, especially
compared with computing explicit indices like array[rows-2:rows, cols-2:cols].
Quiz
Question 7/107/10
Which file system is commonly used in Windows and supports file permissions?
A NTFS
B FAT32
C HFS+
D EXT4
A NTFS
B FAT32
C HFS+
D EXT4
Check the image below to see the right answer:Select the answer
1 correct answerWindows commonly uses the NTFS (New Technology File System) for internal drives and many external
drives because it supports advanced features required for modern operating systems. One of the most
important features is support forfile and folder permissionsvia Access Control Lists (ACLs). Permissions
enable the OS to enforce security policies by controlling which users and groups can read, write,
execute, modify, or delete specific resources. This is fundamental to multi-user security and is a
standard topic in operating systems and security textbooks.
FAT32 is an older file system designed for simplicity and broad compatibility. It does not provide the
same fine-grained permission model as NTFS, which is why it is often used for removable media where
cross-platform compatibility matters more than access control. HFS+ is historically associated with
Apple’s macOS systems, and EXT4 is widely used on Linux. While these file systems have their own
permission and feature models, they are not the common Windows default for permission-managed
storage in typical Windows deployments.
NTFS also supports journaling (improving reliability after crashes), large file sizes, quotas, compression,
and encryption features (through Windows facilities). In enterprise environments, NTFS permissions
integrate with Windows authentication and directory services, enabling centralized user management.
Therefore, for Windows systems requiring file permissions, NTFS is the correct answer.
drives because it supports advanced features required for modern operating systems. One of the most
important features is support forfile and folder permissionsvia Access Control Lists (ACLs). Permissions
enable the OS to enforce security policies by controlling which users and groups can read, write,
execute, modify, or delete specific resources. This is fundamental to multi-user security and is a
standard topic in operating systems and security textbooks.
FAT32 is an older file system designed for simplicity and broad compatibility. It does not provide the
same fine-grained permission model as NTFS, which is why it is often used for removable media where
cross-platform compatibility matters more than access control. HFS+ is historically associated with
Apple’s macOS systems, and EXT4 is widely used on Linux. While these file systems have their own
permission and feature models, they are not the common Windows default for permission-managed
storage in typical Windows deployments.
NTFS also supports journaling (improving reliability after crashes), large file sizes, quotas, compression,
and encryption features (through Windows facilities). In enterprise environments, NTFS permissions
integrate with Windows authentication and directory services, enabling centralized user management.
Therefore, for Windows systems requiring file permissions, NTFS is the correct answer.
Quiz
Question 8/108/10
What is the method for changing an element in a Python list?
A Use square brackets and the equals sign
B Use parentheses and the plus sign
C Use curly brackets and the equals sign
D Use the del keyword and the element’s value
A Use square brackets and the equals sign
B Use parentheses and the plus sign
C Use curly brackets and the equals sign
D Use the del keyword and the element’s value
Check the image below to see the right answer:Select the answer
1 correct answerIn Python, a list is a mutable sequence, meaning its elements can be changed after the list is created.
The standard textbook method for updating a specific element isindex assignment, which uses square
brackets to select the position and the equals sign to assign a new value. For example, if nums = [10, 20,
30], then nums[1] = 99 changes the element at index 1 from 20 to 99, producing [10, 99, 30]. This works
because lists store references to objects and allow those references to be updated in-place.
Option B is incorrect because parentheses are used for function calls and tuples, and the plus sign
typically performs concatenation (creating a new list) rather than modifying an existing element by
position. Option C is incorrect because curly brackets denote dictionaries or sets, not lists. Option D is
incorrect because del removes elements by index or slice (for example, del nums[1]), and it does not
delete by “the element’s value” unless you first find the index. Deleting is not the same as changing;
deletion reduces the list’s length and shifts later indices.
Index assignment is fundamental in list manipulation and appears in standard algorithms: updating
counters, replacing sentinel values, editing collections, and implementing in-place transformations
efficiently without allocating a new list.
The standard textbook method for updating a specific element isindex assignment, which uses square
brackets to select the position and the equals sign to assign a new value. For example, if nums = [10, 20,
30], then nums[1] = 99 changes the element at index 1 from 20 to 99, producing [10, 99, 30]. This works
because lists store references to objects and allow those references to be updated in-place.
Option B is incorrect because parentheses are used for function calls and tuples, and the plus sign
typically performs concatenation (creating a new list) rather than modifying an existing element by
position. Option C is incorrect because curly brackets denote dictionaries or sets, not lists. Option D is
incorrect because del removes elements by index or slice (for example, del nums[1]), and it does not
delete by “the element’s value” unless you first find the index. Deleting is not the same as changing;
deletion reduces the list’s length and shifts later indices.
Index assignment is fundamental in list manipulation and appears in standard algorithms: updating
counters, replacing sentinel values, editing collections, and implementing in-place transformations
efficiently without allocating a new list.
Quiz
Question 9/109/10
Which is the most powerful command line interface on Windows systems?
A Task Manager
B Command Prompt
C Control Panel
D PowerShell
A Task Manager
B Command Prompt
C Control Panel
D PowerShell
Check the image below to see the right answer:Select the answer
1 correct answerOn Windows,PowerShellis generally regarded as the most powerful command-line environment because
it is both a shell and a scripting language designed for system administration and automation. Traditional
Command Prompt focuses on running console commands and batch files with plain-text input and
output. PowerShell, by contrast, uses an object-oriented pipeline: commands (calledcmdlets) output
structured objects rather than raw text. This enables more reliable scripting and data manipulation, since
you can filter, sort, and transform results without fragile text parsing.
Textbooks covering operating systems and administration emphasize automation and management at
scale. PowerShell integrates tightly with Windows management technologies, such as WMI/CIM, the
registry, services, event logs, and Active Directory environments. It also supports remote management,
scripting modules, robust error handling, and modern security features. This makes it particularly suitable
for tasks like provisioning users, configuring machines, auditing systems, and orchestrating
deployments.
The other options are not command-line interfaces in the same sense. Task Manager is a GUI tool for
viewing processes and performance. Control Panel is also GUI-based for system configuration.
Command Prompt is a command line interface, but it is less capable for complex administration
compared to PowerShell’s scripting and object pipeline.
Therefore, from a computer science and systems perspective, PowerShell is the most powerful Windows
CLI environment among the choices.
it is both a shell and a scripting language designed for system administration and automation. Traditional
Command Prompt focuses on running console commands and batch files with plain-text input and
output. PowerShell, by contrast, uses an object-oriented pipeline: commands (calledcmdlets) output
structured objects rather than raw text. This enables more reliable scripting and data manipulation, since
you can filter, sort, and transform results without fragile text parsing.
Textbooks covering operating systems and administration emphasize automation and management at
scale. PowerShell integrates tightly with Windows management technologies, such as WMI/CIM, the
registry, services, event logs, and Active Directory environments. It also supports remote management,
scripting modules, robust error handling, and modern security features. This makes it particularly suitable
for tasks like provisioning users, configuring machines, auditing systems, and orchestrating
deployments.
The other options are not command-line interfaces in the same sense. Task Manager is a GUI tool for
viewing processes and performance. Control Panel is also GUI-based for system configuration.
Command Prompt is a command line interface, but it is less capable for complex administration
compared to PowerShell’s scripting and object pipeline.
Therefore, from a computer science and systems perspective, PowerShell is the most powerful Windows
CLI environment among the choices.
Quiz
Question 10/1010/10
Given the following code, what is the expected output?
A [10, 20, 30, 40]
B [1, 10]
C [1, 2, 3, 4]
D array([10, 20, 30, 40])
A [10, 20, 30, 40]
B [1, 10]
C [1, 2, 3, 4]
D array([10, 20, 30, 40])
Check the image below to see the right answer:Select the answer
1 correct answerIn NumPy, a 2D array can be visualized as a table of rows and columns. When you write np_2d[0], you
are usingzero-based indexingto select thefirst rowof that 2D array. This is a standard convention in
Python and many other programming languages: index 0 refers to the first element, index 1 to the
second, and so on.
Therefore, np_2d[0] returns all the elements in row 0.
With a typical construction such as np_2d = np.array([[1, 2, 3, 4], [10, 20, 30, 40]]), the first row is [1, 2,
3, 4], so printing np_2d[0] displays that row. NumPy returns the row as a 1D NumPy array, and when
printed it often appears in bracket form like [1 2 3 4] (spaces rather than commas are common in
NumPy’s display).
Conceptually, however, the contents are exactly the first row values, matching option C.
Option A and D show the second row (index 1), not the first. Option B incorrectly suggests a column
extraction rather than a row selection.
are usingzero-based indexingto select thefirst rowof that 2D array. This is a standard convention in
Python and many other programming languages: index 0 refers to the first element, index 1 to the
second, and so on.
Therefore, np_2d[0] returns all the elements in row 0.
With a typical construction such as np_2d = np.array([[1, 2, 3, 4], [10, 20, 30, 40]]), the first row is [1, 2,
3, 4], so printing np_2d[0] displays that row. NumPy returns the row as a 1D NumPy array, and when
printed it often appears in bracket form like [1 2 3 4] (spaces rather than commas are common in
NumPy’s display).
Conceptually, however, the contents are exactly the first row values, matching option C.
Option A and D show the second row (index 1), not the first. Option B incorrectly suggests a column
extraction rather than a row selection.
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