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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Python Basics for Data Analysis	32.5%	- File Handling 1. Use the csv module for basic CSV operations 2. Read from and write to files (text, CSV) - Data Structures 1. Work with lists, tuples, dictionaries, and sets 2. Apply common operations and methods to data structures - Python Fundamentals 1. Use variables, data types, and basic operators 2. Define and use functions 3. Implement control flow structures (loops, conditionals)
Topic 2: Working with Data and Performing Simple Analyses	32.5%	- Data Cleaning and Transformation 1. Perform basic data transformation (filtering, sorting, grouping) 2. Handle missing and inconsistent data - Data Analysis with Python Libraries 1. Use the math and statistics modules for basic calculations 2. Perform basic operations with NumPy arrays 3. Utilize the collections module for specialized containers 4. Work with the datetime module for date/time data - Simple Analytical Techniques 1. Calculate descriptive statistics (mean, median, mode) 2. Identify basic patterns and trends in data
Topic 3: Introduction to Data and Data Analysis Concepts	22.5%	- Define and Classify Data 1. Explain how data becomes meaningful 2. Classify data as quantitative or qualitative 3. Differentiate structured, semi-structured, and unstructured data - Data Analysis Process and Workflow 1. Identify common data sources and collection methods 2. Explain the role of data cleaning and preparation 3. Describe the steps of the data analysis process - Data Ethics and Privacy 1. Understand basic data privacy concepts 2. Recognize ethical considerations in data handling
Topic 4: Communicating Insights and Reporting	12.5%	- 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 - Data Visualization 1. Interpret simple data visualizations 2. Recognize common visualization types (bar, line, pie charts) 3. Select appropriate visuals for different data types

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

Question #1

A script attempts to divide two numbers using / and //. The values are 7 and 2. The developer wants to understand the difference between true division and floor division. What are the results respectively?

A. 3 and 4
B. 4 and 3
C. 3 and 3.5
D. 3.5 and 3

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #2

A healthcare provider analyzes patient records to determine that appointment cancellations spike during weather alerts and flu season.
What type of analytics is this?

A. Predictive analytics - it uses weather and illness trends to forecast future cancellations.
B. Prescriptive analytics - it automates patient rescheduling based on cancellation patterns.
C. Diagnostic analytics - it identifies reasons behind patterns in patient behavior.
D. Descriptive analytics - it reports appointment numbers across past seasons.

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Correct Answer: C 🗳️

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Question #3

Which of the following statements about Python functions are correct? (Choose two.)

A. Functions can only return numeric values or strings.
B. If a function does not contain a returnstatement, it returns Noneby default.
C. A function cannot call itself or be passed as an argument to itself.
D. passexecutes the function body and returns its result.
E. Default parameters must always come before required ones in the parameter list.
F. Positional arguments must be passed in the order defined, while keyword arguments can be passed in any order using their parameter names.

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Correct Answer: B,F 🗳️

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Question #4

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. 5, 4, 3, 2, 1
B. 5, 3, 1
C. 4, 2, 0
D. 5, 3

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #5

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.