最實用的PCED-30-02認證考試的學習資料

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Recognize common visualization types (bar, line, pie charts)
  • 2. Interpret simple data visualizations
  • 3. Select appropriate visuals for different data types
- Data Storytelling and Reporting
  • 1. Structure insights as a narrative
  • 2. Present insights with visual and verbal techniques
  • 3. Create clear and concise analytical reports
Topic 2: Working with Data and Performing Simple Analyses32.5%- Data Cleaning and Transformation
  • 1. Handle missing and inconsistent data
  • 2. Perform basic data transformation (filtering, sorting, grouping)
- Simple Analytical Techniques
  • 1. Calculate descriptive statistics (mean, median, mode)
  • 2. Identify basic patterns and trends in data
- Data Analysis with Python Libraries
  • 1. Work with the datetime module for date/time data
  • 2. Perform basic operations with NumPy arrays
  • 3. Use the math and statistics modules for basic calculations
  • 4. Utilize the collections module for specialized containers
Topic 3: Python Basics for Data Analysis32.5%- Python Fundamentals
  • 1. Define and use functions
  • 2. Use variables, data types, and basic operators
  • 3. Implement control flow structures (loops, conditionals)
- File Handling
  • 1. Use the csv module for basic CSV operations
  • 2. Read from and write to files (text, CSV)
- Data Structures
  • 1. Apply common operations and methods to data structures
  • 2. Work with lists, tuples, dictionaries, and sets
Topic 4: Introduction to Data and Data Analysis Concepts22.5%- Data Analysis Process and Workflow
  • 1. Explain the role of data cleaning and preparation
  • 2. Identify common data sources and collection methods
  • 3. Describe the steps of the data analysis process
- Define and Classify Data
  • 1. Explain how data becomes meaningful
  • 2. Differentiate structured, semi-structured, and unstructured data
  • 3. Classify data as quantitative or qualitative
- Data Ethics and Privacy
  • 1. Understand basic data privacy concepts
  • 2. Recognize ethical considerations in data handling

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最新的 Python Institute PCED PCED-30-02 免費考試真題 (Q44-Q49):

問題 #44
A list is reversed using slicing: lst[::-1]. The programmer wants to confirm whether this modifies the original list or creates a new one. What is the correct behavior?

答案：B

解題說明：
Slicing creates a new list object rather than modifying the original. The expression lst[::-1] returns a reversed copy, leaving the original list unchanged.


問題 #45
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?

答案：D

解題說明：
Slicing includes the start index but excludes the end index. Characters at indices 1, 2, and 3 are selected, producing the substring "yth".


問題 #46
A financial technology company is reviewing its data practices to ensure legal and ethical compliance.
Which of the following actions would support responsible data handling and align with regulations like GDPR, HIPAA, and CCPA? (Choose two.)

答案：B,C

解題說明：
Encrypting stored and transmitted data protects sensitive information from unauthorized access and supports regulatory requirements for data security. Providing clear explanations of data usage and obtaining explicit consent ensures transparency and aligns with core principles of data protection regulations such as lawful processing and user rights.


問題 #47
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

答案：D,F

解題說明：
The largest portions of the chart are sleep and school, and together they clearly make up more than half of the day. Leisure appears as a mid-sized segment that is larger than commuting but smaller than school, fitting the description of a moderate portion.


問題 #48
You are given two lists representing daily page views and sign-ups on a website:
views = [120, 130, 128, 700, 115, 123, 119, 680, 122]
signups = [12, 15, 13, 50, 11, 14, 10, 55, 13]
You want to:
- remove outliers (views > 600), and
- calculate correlation between the cleaned lists.
Which code accomplishes this correctly? Select the best answer.

答案：B

解題說明：
It converts the lists to NumPy arrays, builds a boolean mask based on the views threshold to remove outliers, applies the same mask to both arrays so they stay aligned, and then computes the correlation on the cleaned pairs using np.corrcoef.


問題 #49
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