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Python Institute PCED-30-02 Exam Syllabus Topics:

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

Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions:

1. The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

A) Commuting is the second most time-consuming activity.
B) Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.
C) More time is spent commuting than on leisure.
D) School and homework together take up half of the day's time.
E) Leisure and meals combined equal the time spent at school.
F) Sleep and school take up the majority of time in a day.


2. A Python loop uses range(5, 0, -2) to iterate backward. The programmer expects a decreasing sequence. Which values will actually be generated when this loop runs?

A) 4, 2, 0
B) 5, 3
C) 5, 4, 3, 2, 1
D) 5, 3, 1


3. An online retailer collects customer reviews, order transaction logs, and product ratings.
Which of the following correctly classifies these types of data? Select the best answer.

A) Product ratings are quantitative and structured; customer reviews are qualitative and unstructured; transaction logs are structured and quantitative
B) Product ratings are qualitative and structured; customer reviews are qualitative and unstructured; transaction logs are quantitative and semi-structured.
C) Product ratings are qualitative and unstructured; customer reviews are quantitative and structured; transaction logs are semi-structured and qualitative.
D) Product ratings are quantitative and unstructured; customer reviews are structured and qualitative; transaction logs are quantitative and unstructured.


4. A health researcher uses wearable devices to record physical activity and sends a survey to randomly selected participants across age groups.
Why can this approach be effective? Select the best answer.

A) It combines automated data collection with representative sampling, reducing the risk of bias.
B) It relies on observational methods, which are more accurate than surveys or sensors.
C) It limits sampling to one demographic, ensuring high-quality data within a specific group.
D) It uses unstructured interviews to validate automated tracking, improving bias detection.


5. You have collected sales data and want to compute the average using the NumPy library.
Which option correctly shows how to install NumPy and use it in your code to perform this task?

A) To install NumPy:
pip install numpy
Then run this code:
import numpy as np
data = numpy.arr([10, 20, 30])
print(numpy.mean(data))
B) To install NumPy:
pip install numpy as np
Then run this code:
import np
data = np.array([10, 20, 30])
print(np.mean(data))
C) To install NumPy:
from pip install numpy
Then run this code:
import numpy as np
data = np.array([10, 20, 30])
print(np.mean(data))


Solutions:

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

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