Python Institute PCED-30-02 exam - in .pdf

PCED-30-02 pdf
  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Q & A: 52 Questions and Answers
  • PDF Price: $59.99
  • PDF Demo

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  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Q & A: 52 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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  • Exam Code: PCED-30-02
  • Exam Name: PCED - Certified Entry-Level Data Analyst with Python
  • Q & A: 52 Questions and Answers
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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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

1. A loop includes a break statement when a condition is met. The programmer wants to understand how break affects loop execution. What happens when break is executed inside the loop?

A) Loop restarts
B) Loop ends immediately
C) Error
D) Skips one iteration


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


3. You are working with city names entered by users. These names may contain inconsistent capitalization and unwanted spaces.
To standardize the data, you want to:
- Remove any leading or trailing whitespace, and
- Capitalize the first letter of each word (e.g., convert "new york" to "New York").
For example:
" New york " → "New York"
"lOS ANGELES" → "Los Angeles"
You are given a variable citythat contains the raw input.
Which line of code correctly updates the value of cleaned_cityto apply the required transformation? Select the best answer.

A) cleaned_city = city.strip().title()
B) cleaned_city = city.strip().capitalize()
C) cleaned_city = city.upper().replace(" ", "")
D) cleaned_city = city.upper().strip()


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


5. Consider a Python program that assigns a string value "5" to a variable and then attempts to multiply it by an integer 3. The programmer expects numeric multiplication. What will actually happen when the code is executed?

A) 15
B) "555"
C) Error
D) 8


Solutions:

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

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