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Python Institute PCED-30-02 Exam Syllabus Topics:

Section	Weight	Objectives
Working with Data and Performing Simple Analysis	25%	- Data aggregation and grouping 1. Summarizing and grouping datasets - Exploratory data analysis 1. Identifying patterns, trends, and outliers 2. Calculating mean, median, mode, range, variance, standard deviation - Data acquisition and loading 1. Importing data from external sources 2. Reading text, CSV, and structured files - Data cleaning and preparation 1. Formatting and standardizing values 2. Filtering, sorting, transforming data 3. Handling missing values, duplicates, and errors
Data Visualization and Communication	20%	- Principles of effective data visualization 1. Clarity, simplicity, and accuracy 2. Choosing appropriate chart types - 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
Introduction to Data and Data Analysis Concepts	22.5%	- Data types and measurement scales 1. Qualitative vs quantitative data 2. Nominal, ordinal, interval, ratio scales - Definition and classification of data 1. Difference between data, information, and knowledge 2. Process of turning raw data into insights 3. Role of data in decision-making and business - Basic statistical concepts 1. Descriptive vs inferential statistics 2. Population, sample, variable, observation - Data lifecycle and ethical considerations 1. Data collection, storage, processing, usage, and sharing 2. Privacy, security, bias, and fairness in data
Python Basics for Data Analysis	32.5%	- Introduction to NumPy 1. Arrays, basic operations, indexing, slicing - Control flow and functions 1. Defining and calling functions, parameters, return values 2. Conditional statements, loops, iteration 3. Basic exception handling - Built-in modules for data work 1. math, statistics, datetime, collections, csv - Core Python syntax and data types 1. Lists, tuples, sets, dictionaries 2. Variables, numbers, strings, booleans

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

1. 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.

A)

B)

C)

2. 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?

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

3. Consider the following Python code:

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

A) [20, 30, 40]
1
[1, 2, 4, 5, 6]
B) [10, 20, 30, 40]
0
[1, 2, 3, 4, 5, 6]
50
C) [20, 30, 40]
1
[1, 2, 4, 5, 6]
50
D) [10, 20, 30, 40]
1
[1, 2, 4, 5, 6]
50

4. A list is defined as [1, 2, 3]. The programmer uses the method .append([4, 5]). What will the resulting list look like after execution?

A) Error
B) [4,5,1,2,3]
C) [1,2,3,4,5]
D) [1,2,3,[4,5]]

5. A loop is designed using range(1, 6, 2) to iterate through numbers. The developer wants to know exactly which values will be generated during execution. Which sequence correctly represents the values produced?

A) 1, 3
B) 1, 2, 3, 4, 5
C) 1, 3, 5
D) 2, 4, 6

Solutions:

Question # 1
Answer: C

Question # 2
Answer: D

Question # 3
Answer: A

Question # 4
Answer: D

Question # 5
Answer: C