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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Introduction to Data and Data Analysis Concepts22.5%- Data Ethics and Privacy
  • 1. Recognize ethical considerations in data handling
  • 2. Understand basic data privacy concepts
- Define and Classify Data
  • 1. Classify data as quantitative or qualitative
  • 2. Differentiate structured, semi-structured, and unstructured data
  • 3. Explain how data becomes meaningful
- 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
Topic 2: Working with Data and Performing Simple Analyses32.5%- Data Cleaning and Transformation
  • 1. Handle missing and inconsistent data
  • 2. Perform basic data transformation (filtering, sorting, grouping)
- Data Analysis with Python Libraries
  • 1. Perform basic operations with NumPy arrays
  • 2. Work with the datetime module for date/time data
  • 3. Use the math and statistics modules for basic calculations
  • 4. Utilize the collections module for specialized containers
- Simple Analytical Techniques
  • 1. Identify basic patterns and trends in data
  • 2. Calculate descriptive statistics (mean, median, mode)
Topic 3: 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. Define and use functions
  • 2. Use variables, data types, and basic operators
  • 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
Topic 4: Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Interpret simple data visualizations
  • 2. Recognize common visualization types (bar, line, pie charts)
  • 3. Select appropriate visuals for different data types
- Data Storytelling and Reporting
  • 1. Create clear and concise analytical reports
  • 2. Structure insights as a narrative
  • 3. Present insights with visual and verbal techniques

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q47-Q52):

NEW QUESTION # 47
A list is reversed using slicing: lst[::-1]. The programmer wants to confirm whether this modifies the original list or creates a new one. What is the correct behavior?

Answer: A

Explanation:
Slicing creates a new list object rather than modifying the original. The expression lst[::-1] returns a reversed copy, leaving the original list unchanged.


NEW QUESTION # 48
You are writing a function named process_data()to read and process numerical input from a file. The function must:
- read the file data.txt,
- attempt to convert the first line into an integer,
- handle file, conversion, or index-related exceptions,
- print the value only if no error occurs,
- and always print a final message after execution.
Which implementation correctly and robustly meets all these conditions? Select the best answer.

Answer: B

Explanation:
It wraps file reading and integer conversion in a try block, catches the relevant file, conversion, and indexing exceptions, prints the value only in the no-error path using an else block, and uses a finally block to always print the final message.


NEW QUESTION # 49
How do the analysis and visualization stages of the data lifecycle typically work together?

Answer: C

Explanation:
Analysis involves examining processed data to uncover patterns, trends, and insights, and visualization presents those findings in graphical form so stakeholders can clearly understand and act on the results.


NEW QUESTION # 50
A Python script includes the expression not False and True. The developer is unsure how logical operators are evaluated in terms of precedence. What will be the final Boolean result of this expression?

Answer: D

Explanation:
The not operator has higher precedence than and, so not False becomes True first. Then True and True is evaluated, resulting in True as the final Boolean value.


NEW QUESTION # 51
A data analyst exports a cleaned dataset from Python and wants to share it with a colleague for easy use in Excel.
Which file format is best suited for this purpose? Select the best answer.

Answer: A

Explanation:
CSV stores tabular data in a simple plain-text, comma-separated format that is widely supported by spreadsheet applications like Excel, making it ideal for sharing datasets for easy import and analysis.


NEW QUESTION # 52
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