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Python Institute PCAD-31-02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Working with Data Using Python Libraries	30%	- Data Visualization 1. Creating basic charts (line, bar, scatter, histogram) 2. Seaborn introduction 3. Matplotlib basics 4. Customizing plots - Pandas Library 1. GroupBy operations 2. Series and DataFrame structures 3. DataFrame operations (merge, join, concat) 4. Data selection and filtering 5. Handling missing data - NumPy Fundamentals 1. NumPy arrays and operations 2. Basic statistical functions 3. Vectorized operations 4. Array indexing and slicing
Topic 2: Data Analysis Fundamentals	20%	- Data Collection and Preparation 1. Data import/export operations 2. Data cleaning and preprocessing basics 3. Data sources and acquisition methods - Introduction to Data Analysis 1. Data analysis process lifecycle 2. Types of data (structured, unstructured, semi-structured) 3. Data analysis concepts and terminology
Topic 3: Applied Data Analysis Projects	20%	- Data Analysis Workflow 1. Analysis and modeling 2. Results interpretation and presentation 3. Data exploration and cleaning 4. Problem definition - Exploratory Data Analysis (EDA) 1. Descriptive statistics computation 2. Pattern identification 3. Data distribution analysis 4. Correlation analysis
Topic 4: Python Programming for Data Analysis	30%	- Control Flow and Functions 1. Loops (for, while) 2. Conditional statements (if, elif, else) 3. Function definitions and parameters 4. Return values and scope - File Operations 1. Writing to files 2. Reading from files (text, CSV) 3. Context managers (with statement) - Python Data Types and Structures 1. Numbers, strings, booleans 2. Lists, tuples, dictionaries, sets 3. Data type conversions

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q56-Q61):

NEW QUESTION # 56
Why is min-max scaling applied before using algorithms like K-Nearest Neighbors or SVM?

A. To convert strings into numeric values
B. To make all features interpretable as binary values
C. To prevent features with larger scales from dominating distance calculations
D. To compress all values into integers

Answer: C

NEW QUESTION # 57
Which SQL commands can be used to modify the contents of a table's data directly?
(Choose all that apply)

A. UPDATE
B. INSERT
C. SELECT
D. DELETE

Answer: A,B

NEW QUESTION # 58
What is the primary reason for converting all categorical labels to lowercase during the data cleaning process?

A. To make string comparison operations slower
B. To avoid treating the same category as different due to case differences
C. To reduce memory usage in the dataset
D. To improve data visualization aesthetics

Answer: B

NEW QUESTION # 59
What is one potential risk of dynamically constructing SQL queries using string concatenation in Python scripts?

A. Missing foreign key constraints
B. Exposure to SQL injection attacks
C. Increased memory usage
D. Slower database performance

Answer: B

NEW QUESTION # 60
What is the primary advantage of using web scraping as a data collection method in business analytics?

A. It allows automation of data collection from public sources
B. It ensures compliance with privacy laws
C. It eliminates the need for data cleaning
D. It guarantees real-time data accuracy

Answer: A

NEW QUESTION # 61
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