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| Section | Objectives |
|---|---|
| Topic 1: Basic Program Design | - Explain how to store, access, and manipulate data in lists - Use functions, methods, and packages to leverage programming language - Identify variables and data types within a programming language |
| Topic 2: Data Profiling | - Apply fundamental concepts and subsetting techniques to a dataset - Utilize a programming language to manipulate arrays and discover insights |
| Topic 3: Algorithm Efficiency | - Choose an appropriate algorithm searching method based on a given scenario - Choose an appropriate sorting algorithm method based on a given scenario - Describe the relationships between algorithm complexity and data structures |
| Topic 4: OS Fundamentals | - Describe fundamental principles and core concepts of operating systems - Identify common privacy and security concepts that could be implemented in operating systems - Demonstrate various techniques and tools to manage operating systems |
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質問 # 46
Which aspect of a security policy would define the ramifications of abusing company resources?
正解：A
解説：
AnAcceptable 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.
質問 # 47
Given the following code, what is the expected output?
正解：C
解説：
In 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.
質問 # 48
What is another term for the inputs into a function?
正解：B
解説：
In programming, a function takes inputs, performs computation, and may return an output. The standard term for a function's inputs isarguments(also commonly discussed alongside the closely related termparameters).
Textbooks typically distinguish the two:parametersare the names listed in the function definition, while argumentsare the actual values supplied when the function is called. For example, in def f(x, y):, x and y are parameters. In the call f(3, 5), 3 and 5 are arguments. Many introductory materials use "arguments" informally to refer to the inputs overall, which matches the wording of this question.
Options A, B, and C do not fit the textbook definition. "Variables" is too broad; inputs can be literals, expressions, or variables, but the conceptual role is "arguments." "Procedures" are callable units of code (often used in some languages to mean functions without return values), not the inputs. "Outputs" refers to returned results, not what you pass in.
Understanding arguments is important because it connects to call semantics, scope, and correctness.
Different languages support positional arguments, keyword arguments, default values, and variadic arguments (e.g., *args, **kwargs in Python). This flexibility shapes API design and influences how programmers structure reusable code.
質問 # 49
Which Python function is used to display the data type of a given variable?
正解：D
解説：
Python is a dynamically typed language, meaning variables do not require explicit type declarations; instead, objects carry type information at runtime. To inspect the type of an object, Python provides the built-in function type(). When you pass a variable or value into type(), it returns the object's class, which represents its data type. For example, type(5) returns <class 'int'>, type(3.14) returns <class 'float'>, and type("hello") returns <class 'str'>. This is commonly used in debugging, learning exercises, and when writing functions that must behave differently depending on input types.
Textbook discussions often pair type() with Python's object model: everything in Python is an object, and each object is an instance of some class. type() reveals that class. In addition, type() can be used in more advanced ways, such as dynamic class creation, but its foundational educational use is type inspection.
The other options are not correct because GetVar(), Show(), and Data() are not standard Python built- ins for type checking. While developers can define functions with those names, they are not part of Python's core language or standard library in the sense required by the question. For typical coursework and professional Python usage, the correct and universally accepted function is type().
質問 # 50
What happens if one element of a NumPy array is changed to a string?
正解：C
解説：
A central rule in NumPy is that an ndarray has a single, fixed data type called itsdtype. That dtype is chosen when the array is created (for example, int64, float64, etc.), and it normally does not change just because you assign a new value into one element. When you attempt an assignment, NumPy tries tocastthe assigned value into the array's existing dtype. If the cast is possible, the assignment succeeds; if the cast is impossible, NumPy raises an error.
So, if you have a numeric array such as arr = np.array([1, 2, 3]), its dtype is an integer type. Trying arr[0] =
"hello" cannot be converted into an integer, so NumPy raises a ValueError (a casting/conversion error). This is exactly the behavior textbooks highlight when contrasting NumPy arrays with Python lists: lists can hold mixed types freely, but NumPy arrays trade that flexibility for speed and memory efficiency via uniform typing.
Option A is a common misconception. While NumPy may "upcast" values to a more general dtype at array creation time when mixed types are provided (e.g., numbers and strings in the same constructor), a pre-existing numeric array will not automatically convert itself into a string array during a single- element assignment. Options C and D do not reflect NumPy's assignment rules.
質問 # 51
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