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| Section | Objectives |
|---|---|
| Topic 1: Data Profiling | - Apply fundamental concepts and subsetting techniques to a dataset - Utilize a programming language to manipulate arrays and discover insights |
| Topic 2: Basic Program Design | - Use functions, methods, and packages to leverage programming language - Explain how to store, access, and manipulate data in lists - Identify variables and data types within a programming language |
| Topic 3: Algorithm Efficiency | - Describe the relationships between algorithm complexity and data structures - Choose an appropriate sorting algorithm method based on a given scenario - Choose an appropriate algorithm searching method based on a given scenario |
| 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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NEW QUESTION # 68
What code would print a subarray of the first 5 elements in numpy_array?
Answer: A
Explanation:
NumPy arrays support slicing using the same start:stop convention as Python sequences. To take the first five elements, you want indices 0 through 4. The slice numpy_array[:5] means "start from the beginning (default start is 0) and stop before index 5." Because the stop index is exclusive, this returns exactly the first five elements. Printing that slice with print(numpy_array[:5]) displays a 1D view (or copy depending on context) containing those elements.
Option A, numpy_array[1:5], starts at index 1, so it returns elements 1 through 4-only four elements-and it excludes the element at index 0, so it is not the first five elements. Options B and D are incorrect because NumPy arrays do not provide a .get() method for slicing in this manner; .get() is a method associated with dictionaries, not arrays.
Textbooks stress slicing because it is efficient and expressive, especially in data analysis. With slicing, you can take prefixes, suffixes, windows, or regularly spaced samples without writing loops. In NumPy, slicing is particularly important because many slices create views into the same underlying data buffer, enabling memory-efficient operations on large datasets. Understanding inclusive start and exclusive stop boundaries is critical to avoid off-by-one mistakes and to work correctly with batches and segments of numerical data.
NEW QUESTION # 69
Which aspect of a security policy would define the ramifications of abusing company resources?
Answer: B
Explanation:
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.
NEW QUESTION # 70
What is the time complexity of a binary search algorithm?
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