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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Working with Data and Performing Simple Analyses	32.5%	- Data Analysis with Python Libraries 1. Use the math and statistics modules for basic calculations 2. Utilize the collections module for specialized containers 3. Work with the datetime module for date/time data 4. Perform basic operations with NumPy arrays - 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)
Introduction to Data and Data Analysis Concepts	22.5%	- Data Ethics and Privacy 1. Understand basic data privacy concepts 2. Recognize ethical considerations in data handling - Data Analysis Process and Workflow 1. Identify common data sources and collection methods 2. Describe the steps of the data analysis process 3. Explain the role of data cleaning and preparation - 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
Communicating Insights and Reporting	12.5%	- 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
Python Basics for Data Analysis	32.5%	- Python Fundamentals 1. Define and use functions 2. Implement control flow structures (loops, conditionals) 3. Use variables, data types, and basic operators - Data Structures 1. Work with lists, tuples, dictionaries, and sets 2. Apply common operations and methods to data structures - File Handling 1. Use the csv module for basic CSV operations 2. Read from and write to files (text, CSV)

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

1. You are creating a presentation slide to communicate findings about student stress levels across four categories over a six-month period. You include the following line graph in your presentation:

Your goal is to help your audience clearly understand trends in stress levels over time.
What is the highest problem with this visual presentation? Select the best answer.

A) The lines are too light and similar in color, making it difficult to distinguish between trends.
B) The font used in the chart is hard to read; using larger, uppercase text would improve clarity.
C) The months should be replaced with week numbers to provide more detailed insight.
D) The chart should be in 3D format to show depth and highlight differences more clearly.
E) The graph doesn't explain what each stress level means or show exact values for each month, which limits interpretation.

2. A student writes a program using input() to collect user data, then tries to add 5 to the input value without conversion. The program crashes. What is the most likely cause of this behavior?

A) input returns float
B) input returns int
C) input returns string
D) Syntax error

3. You are given a short Python script that uses both arithmetic and assignment operators. The variable x is initialized as 4, then updated using x *= 2 + 3. What will be printed when the final value of x is displayed?

A) 14
B) 10
C) 24
D) 20

4. A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?

A) Error
B) 0
C) 1
D) None

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