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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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

1. You are given the following list of daily step counts:
steps = [8230, 9020, 7640, 8760, 10020, 2546, 9817]
Your task is to calculate:
- the standard deviation of the step counts,
- the average rounded up to the nearest whole number, and
- the median of the step counts.
Which code snippet correctly performs all three tasks? Select the best answer.
import statistics

A) import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics
B) import math
print(statistics.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))
C) import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
D) import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics


2. An e-commerce site records every product view and purchase.
Which of the following best describes how these logs become marketing insights?

A) Raw event logs are validated, organized, and compiled into datasets - like timestamped user actions - which then support system debugging.
B) Raw event logs are structured, analyzed, and interpreted into information - like conversion rates by product - which then builds knowledge of customer preferences.
C) Raw event logs are stored, archived, and indexed - like by user ID and session - which then facilitate audit trails.
D) Raw event logs are filtered, aggregated, and formatted into summaries - like total visits per category - which then provide traffic reports.


3. A programmer writes a script to test operator precedence using the expression 3 + 4 * 2 ** 2. The goal is to evaluate the result correctly based on Python's operator hierarchy rules. What result should the script produce?

A) 49
B) 35
C) 28
D) 19


4. You are reviewing a report that compares the number of weekly client meetings and project completion rates across teams. The table below summarizes the data for each team:

Which statement best describes the data shown above? Select the best answer.

A) "Teams with 5-6 weekly meetings tended to complete more projects than those with very high or very low meeting counts."
B) The more meetings a team had, the more projects they finished, especially in high-performing teams like Omega and Delta."
C) "Gamma and Omega were outliers that inflated the meeting average, but most teams finished about 3 projects per month."
D) "Project completion numbers were nearly identical across all teams, averaging 3.25 per month."


5. A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?

A) False
B) None
C) Error
D) True


Solutions:

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

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