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WGU Foundations-of-Computer-Science Exam Syllabus Topics:

SectionObjectives
Operating Systems & Architecture- OS Fundamentals
  • 1. Memory management concepts
    • 2. Process states and scheduling basics
      - System Architecture
      • 1. Hardware vs software abstraction
        • 2. Von Neumann architecture basics
          Data & Security Basics- Data Handling
          • 1. Basic database concepts overview
            • 2. Data profiling concepts
              - Security Fundamentals
              • 1. Encryption basics (at rest vs in transit)
                • 2. Basic cybersecurity threats and mitigation
                  Programming Foundations- Language Concepts Overview
                  • 1. Compiled vs interpreted languages
                    • 2. Programming paradigms overview
                      - Programming Concepts
                      • 1. Variables, data types, expressions
                        • 2. Control flow (if/else, loops)
                          • 3. Basic pseudocode interpretation
                            Computer Science Fundamentals- Data Structures Introduction
                            • 1. Arrays and lists
                              • 2. Basic sorting and searching concepts
                                - Core CS Concepts
                                • 1. Basic programming logic and algorithms
                                  • 2. Algorithm efficiency and Big-O basics
                                    • 3. Computational thinking and problem solving

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                                      WGU Foundations of Computer Science Sample Questions (Q19-Q24):

                                      NEW QUESTION # 19
                                      Which character is used to indicate a range of values to be sliced into a new list?

                                      Answer: B

                                      Explanation:
                                      In Python, slicing is the standard mechanism for extracting arangeof elements from a sequence type such as a list, string, or tuple. The character that signals a slice range is thecolon:. The general slice syntax is sequence
                                      [start:stop:step]. Most commonly, you see sequence[start:stop], where start is the index to begin from (inclusive) and stop is the index to end at (exclusive). This "inclusive start, exclusive stop" rule is emphasized in textbooks because it makes slice lengths easy to reason about: when step is 1, the number of elements returned is stop - start.
                                      For example, if items = ["a", "b", "c", "d", "e"], then items[1:4] returns ["b", "c", "d"]. Omitting start defaults to the beginning (items[:3] gives the first three elements), and omitting stop defaults to the end (items[2:] gives everything from index 2 onward). The optional step supports patterns like items[::2] for every other element, and negative steps can reverse a sequence (items[::-1]).
                                      The other characters do not define ranges in Python slicing: , separates items (or indices in multidimensional structures), + is addition/concatenation, and = is assignment. The colon is the slicing operator that indicates a range.


                                      NEW QUESTION # 20
                                      Given the following code, what is the expected output?

                                      Answer: B

                                      Explanation:
                                      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.


                                      NEW QUESTION # 21
                                      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 # 22
                                      Which statement describes the relationship between trees and graphs?

                                      Answer: B

                                      Explanation:
                                      In discrete mathematics and computer science, atreeis a special kind ofgraph. The standard graph-theory definition is that a tree is aconnected, acyclicundirected graph. "Acyclic" means it containsno cycles, i.e., you cannot start at a vertex, follow a sequence of edges, and return to the starting vertex without repeating edges in a way that forms a loop. (Wikipedia) This property is exactly what makes option D correct.
                                      The other options contradict the definition. If a structure has cycles, it is not a tree (though it may still be a graph). If it has unconnected nodes, it is not connected; such a structure is more like aforest(a disjoint union of trees) rather than a single tree. (Wikipedia) The idea of "levels" belongs to a particular computer-science representation called arooted tree, where one node is chosen as the root and nodes can be assigned depths
                                      /levels based on distance from the root. But levels are not required in the abstract definition of a tree as a graph; they arise from choosing a root and orientation for convenience in algorithms like BFS/DFS, heaps, and parse trees.
                                      So, the relationship is: every tree is a graph with extra structure-specifically, no cycles and (typically) connectivity-and the "no cycles" rule is the key distinguishing feature. (Discrete Mathematics)


                                      NEW QUESTION # 23
                                      What type of encryption is provided by encryption utilities built into the file system?

                                      Answer: C

                                      Explanation:
                                      File system encryption utilities are designed to protect datastored on a disk-for example, files on an SSD, HDD, or other persistent storage. This protection is calledencryption at rest. The key idea is that if an attacker steals the physical drive, gains access to a powered-off machine, or otherwise reads storage directly, the raw bytes on disk remain unreadable without the correct cryptographic key. Common textbook examples include full-disk encryption and per-file encryption supported by operating systems and file systems.
                                      This differs fromencryption in motion(also called encryption in transit), which protects data while it is being transmitted over networks, such as via TLS/HTTPS, VPNs, or secure messaging protocols. File system utilities do not primarily address network transmission; they address stored data confidentiality. Option B,
                                      "encryption authentication," is not a standard category; authentication is a security goal often achieved using mechanisms like digital signatures, MACs, certificates, and protocol handshakes, not a type of file system encryption. Option D, steganography, is the practice of hiding information within other data (like images or audio) rather than encrypting it for confidentiality.
                                      In short, file system encryption utilities aim to ensure that stored files remain confidential if storage is accessed without authorization, which is precisely the definition of encryption at rest.


                                      NEW QUESTION # 24
                                      ......

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