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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Handle missing and inconsistent data
  • 2. Perform basic data transformation (filtering, sorting, grouping)
Topic 2: 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. 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. Describe the steps of the data analysis process
  • 2. Explain the role of data cleaning and preparation
  • 3. Identify common data sources and collection methods
Topic 3: 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
- 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)
Topic 4: Communicating Insights and Reporting12.5%- 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
- Data Visualization
  • 1. Select appropriate visuals for different data types
  • 2. Interpret simple data visualizations
  • 3. Recognize common visualization types (bar, line, pie charts)

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q39-Q44):

NEW QUESTION # 39
A government agency collects citizen data for various public services.
What is the primary reason for emphasizing careful data management throughout the entire data lifecycle in this context? Select the best answer.

Answer: B

Explanation:
Careful data management across the entire lifecycle ensures high data quality for reliable public services, protects sensitive citizen information from misuse, and maintains compliance with legal and regulatory data protection requirements.


NEW QUESTION # 40
Below are six possible summaries for your presentation:
- Summary 1: "The data revealed a moderate positive correlation between age and recycling frequency. While 72% of students reported recycling paper regularly, only 39% reported recycling plastic."
- Summary 2: "Analysis showed notable differences in recycling habits by material type, with paper being most recycled and plastic least recycled."
- Summary 3: "Older kids recycled more than younger ones. Paper was the most recycled item- plastic got forgotten a lot."
- Summary 4: "Student responses showed positive environmental habits overall, though participation varied by waste type."
- Summary 5: "A lot of students said they recycle. Some didn't answer every question, so we couldn't figure out everything."
- Summary 6: "We asked more than 300 students about recycling. Most said they recycle paper, but way fewer recycle plastic." Which communication style is the best fit for Group A (data scientists) and Group B (12-year- olds), respectively? Select the best answer.

Answer: F

Explanation:
The first summary uses precise statistical language and quantitative detail appropriate for data scientists. The third summary uses simpler, more conversational language that is easier for 12- year-olds to understand.


NEW QUESTION # 41
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: C

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 # 42
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?

Answer: B

Explanation:
Adding an integer and a float produces a float result, so checking that the type of the sum is float evaluates to True. The variable holding 3.0 is a float, so the isinstance check for float also evaluates to True.


NEW QUESTION # 43
A program uses slicing on a string "Python". The expression s[1:4] is evaluated. Which substring will be returned?

Answer: C

Explanation:
Slicing includes the start index but excludes the end index. Characters at indices 1, 2, and 3 are selected, producing the substring "yth".


NEW QUESTION # 44
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