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

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

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WGU Foundations of Computer Science Sample Questions (Q61-Q66):

NEW QUESTION # 61
What is the name of the tool that can allow a device to run more than one operating system at a time as virtual machines?

A. Hypervisor
B. Bootloader
C. System Restore
D. Partition Manager

Answer: A

Explanation:
Ahypervisoris the software layer that enables virtualization-running multiple operating systems concurrently on the same physical hardware as separate, isolated virtual machines (VMs). Operating systems textbooks describe the hypervisor as managing and multiplexing core hardware resources such as CPU, memory, storage, and I/O devices among multiple guest operating systems. Each VM behaves as if it has its own hardware, while the hypervisor enforces isolation and schedules resource usage.
Hypervisors come in two broad categories.Type 1 (bare-metal)hypervisors run directly on the hardware (common in data centers), whileType 2 (hosted)hypervisors run as applications on top of a host OS (common on desktops). In both cases, the hypervisor is the key tool that makes "more than one OS at a time" possible.
System Restore is a recovery feature, not a virtualization platform. A partition manager can split a disk into multiple partitions, which can support dual-boot setups, but that runs only one OS at a time, not concurrently as VMs. A bootloader selects which OS to start at boot time; again, that is not simultaneous virtualization. Therefore, the correct tool that allows running multiple operating systems simultaneously as virtual machines is the hypervisor.

NEW QUESTION # 62
Which aspect is excluded from a NumPy array's structure?

A. The encryption key of the array
B. The shape of the array
C. The data type or dtype pointer
D. The data pointer

Answer: A

Explanation:
A NumPy ndarray is designed for efficient numerical computing, and its structure is defined by metadata required to interpret a contiguous (or strided) block of memory as an n-dimensional array. Textbooks and NumPy's own conceptual model describe key components such as: adata buffer(where the raw bytes live), a data pointer(reference to the start of that buffer), thedtype(which specifies how to interpret each element's bytes-e.g., int32, float64), theshape(the size in each dimension), andstrides(how many bytes to step in memory to move along each dimension). Together, these allow fast indexing, slicing, and vectorized operations without Python-level loops.
Options A, B, and C are all part of what an array must track to function correctly: the array must know where its data is, how it is laid out (shape/strides), and how to interpret bytes (dtype). In contrast, anencryption key is not a concept that belongs to the internal representation of a numerical array. Encryption is a security mechanism applied at storage or transport layers (for example, encrypting a file on disk or encrypting data sent over a network), not something built into the in-memory structure of a NumPy array object.
Therefore, the aspect excluded from a NumPy array's structure is the encryption key.

NEW QUESTION # 63
What is the time complexity of a binary search algorithm?

A. O(n
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