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

SectionWeightObjectives
Topic 1: Computer Architecture & Organization15%- Instruction sets and execution cycles
- CPU, memory, I/O systems
- Memory hierarchy and performance
- Von Neumann architecture
Topic 2: Discrete Mathematics & Logic25%- Boolean algebra and digital logic
- Proof techniques and mathematical induction
- Propositional and predicate logic
- Set theory, relations, functions
Topic 3: Data Structures20%- Primitive and composite data types
- Data storage and retrieval principles
- Arrays, linked lists, stacks, queues
- Trees, graphs, hash tables
Topic 4: Algorithms & Complexity25%- Algorithm design and analysis
- Big O notation, time and space complexity
- Sorting and searching algorithms
- Recursion and iterative structures
Topic 5: Software Engineering & Programming Basics15%- Testing and debugging fundamentals
- Programming paradigms
- Software development lifecycle
- Basic syntax and control structures

WGU Foundations of Computer Science Sample Questions:

Question 1

What is the likely cause if a default Python configuration does not recognize a NumPy array as an allowed data structure?

A. The array module is not imported.
B. The Python version is outdated.
C. The NumPy package is not present.
D. The Python interpreter is misconfigured.


Question 2

Which sorting algorithm works by finding the smallest or largest element in an unsorted part of a list and moving it to the sorted part of the list?

A. Radix sort
B. Heap sort
C. Quicksort
D. Selection sort


Question 3

What is an ndarray in Python?

A. An n-dimensional array object provided by the NumPy library.
B. A built-in Python data array used to store collections of items.
C. A native Python object that represents a tree-like hierarchical data structure.
D. A module that provides network socket functions similar to XML.


Question 4

How can a user subset a NumPy array bmi to only include values over 23?

A. bmi[bmi > 23]
B. bmi.get_values(>23)
C. bmi.select(23)
D. bmi.where(bmi > 23)


Question 5

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[0, 4]
B. np_2d[1, 3]
C. np_2d[3, 1]
D. np_2d[4, 1]


Solutions:

Question 1
Answer: C
Question 2
Answer: D
Question 3
Answer: A
Question 4
Answer: A
Question 5
Answer: B

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