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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Python Basics for Data Analysis32.5%- Python Fundamentals
  • 1. Define and use functions
  • 2. Use variables, data types, and basic operators
  • 3. Implement control flow structures (loops, conditionals)
- 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
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
- Simple Analytical Techniques
  • 1. Calculate descriptive statistics (mean, median, mode)
  • 2. Identify basic patterns and trends in data
- Data Cleaning and Transformation
  • 1. Perform basic data transformation (filtering, sorting, grouping)
  • 2. Handle missing and inconsistent data
Communicating Insights and Reporting12.5%- Data Visualization
  • 1. Recognize common visualization types (bar, line, pie charts)
  • 2. Interpret simple data visualizations
  • 3. Select appropriate visuals for different data types
- Data Storytelling and Reporting
  • 1. Structure insights as a narrative
  • 2. Create clear and concise analytical reports
  • 3. Present insights with visual and verbal techniques
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. Classify data as quantitative or qualitative
  • 2. Explain how data becomes meaningful
  • 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

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

1. An online retailer collects customer reviews, order transaction logs, and product ratings.
Which of the following correctly classifies these types of data? Select the best answer.

A) Product ratings are quantitative and unstructured; customer reviews are structured and qualitative; transaction logs are quantitative and unstructured.
B) Product ratings are quantitative and structured; customer reviews are qualitative and unstructured; transaction logs are structured and quantitative
C) Product ratings are qualitative and unstructured; customer reviews are quantitative and structured; transaction logs are semi-structured and qualitative.
D) Product ratings are qualitative and structured; customer reviews are qualitative and unstructured; transaction logs are quantitative and semi-structured.


2. 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?

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


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) 24
B) 10
C) 20
D) 14


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) 0
B) None
C) Error
D) 1


5. A dictionary is defined as d = {"a":1, "b":2}. The programmer accesses d["c"]. What happens when this line executes?

A) Returns None
B) Adds key automatically
C) Returns 0
D) Raises KeyError


Solutions:

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

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