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Python Institute PCED-30-02 Exam Syllabus Topics:

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

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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q44-Q49):

NEW QUESTION # 44
A Python script checks membership using "a" in "apple". The developer wants to understand how membership works for strings. What result will this expression produce?

Answer: D

Explanation:
The in operator checks for substring presence. Since the character "a" exists in "apple", the expression evaluates to True, demonstrating how membership works for strings in Python.


NEW QUESTION # 45
Consider the following Python code:

What will be printed when the code above is executed?
40

Answer: D

Explanation:
The last element of the original list is 50. The slice from index 1 up to (but not including) index 4 is
[20, 30, 40]. After removing 30 and appending 60, the list contains one occurrence of 10, and integer division by 10 produces [1, 2, 4, 5, 6].


NEW QUESTION # 46
You want to safely read the contents of a file named records.txtand store them in a list. Your requirements are:
- The file should be automatically closed after reading,
- The code should check whether the file exists before opening it, and
- It should handle missing file errors gracefully.
Which of the following is the most appropriate way to accomplish this task in Python? Select the best answer.

Answer: A

Explanation:
It uses a context manager to automatically close the file after reading and wraps the operation in a try-except block to gracefully handle a missing file error, assigning an empty list if the file is not found.


NEW QUESTION # 47
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 # 48
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: D

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 # 49
......

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