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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Python Basics for Data Analysis32.5%- Core Python syntax and data types
  • 1. Variables, numbers, strings, booleans
  • 2. Lists, tuples, sets, dictionaries
- Control flow and functions
  • 1. Basic exception handling
  • 2. Defining and calling functions, parameters, return values
  • 3. Conditional statements, loops, iteration
- Built-in modules for data work
  • 1. math, statistics, datetime, collections, csv
- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
Working with Data and Performing Simple Analysis25%- Exploratory data analysis
  • 1. Calculating mean, median, mode, range, variance, standard deviation
  • 2. Identifying patterns, trends, and outliers
- Data acquisition and loading
  • 1. Reading text, CSV, and structured files
  • 2. Importing data from external sources
- Data cleaning and preparation
  • 1. Formatting and standardizing values
  • 2. Handling missing values, duplicates, and errors
  • 3. Filtering, sorting, transforming data
- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
Introduction to Data and Data Analysis Concepts22.5%- Data lifecycle and ethical considerations
  • 1. Data collection, storage, processing, usage, and sharing
  • 2. Privacy, security, bias, and fairness in data
- Definition and classification of data
  • 1. Role of data in decision-making and business
  • 2. Process of turning raw data into insights
  • 3. Difference between data, information, and knowledge
- Data types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
- Basic statistical concepts
  • 1. Population, sample, variable, observation
  • 2. Descriptive vs inferential statistics
Data Visualization and Communication20%- Interpreting and presenting results
  • 1. Deriving conclusions and insights
  • 2. Reporting findings clearly and concisely
- Creating basic visualizations
  • 1. Line charts, bar charts, histograms, pie charts
  • 2. Using text and simple plotting tools
- Principles of effective data visualization
  • 1. Choosing appropriate chart types
  • 2. Clarity, simplicity, and accuracy

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q42-Q47):

NEW QUESTION # 42
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: B

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 # 43
A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?

Answer: A

Explanation:
A space is still a valid character in a string. Therefore, the string contains one character, and len("
") returns 1 instead of 0.


NEW QUESTION # 44
A program uses while False: followed by print statements inside the loop. The developer expects output. What will actually happen during execution?

Answer: B

Explanation:
The condition False is evaluated before entering the loop. Since it is always false, the loop body is never executed, and no output is produced.


NEW QUESTION # 45
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?

Answer: A

Explanation:
The / operator performs true division, returning a float result of 3.5. The // operator performs floor division, truncating the decimal part and returning the integer value 3.


NEW QUESTION # 46
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)

Answer: C,F


NEW QUESTION # 47
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