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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q111-Q116):

NEW QUESTION # 111
Which Python construct allows you to iterate over a list of dictionary values and apply conditional logic to accumulate numerical values that meet a certain threshold?

A. filter() function with map
B. while loop with try block
C. lambda expression with reduce
D. for loop with if condition

Answer: D

NEW QUESTION # 112
In supervised learning, what is the primary goal when training a model on labeled data?

A. To cluster data points into similar groups
B. To discover hidden patterns without outputs
C. To learn a function that maps inputs to known outputs
D. To analyze unstructured data formats like text

Answer: C

NEW QUESTION # 113
What is a key advantage of using the Parquet file format over CSV in large-scale data pipelines?

A. Parquet stores data in plain text, making it human-readable
B. Parquet supports schema evolution and columnar storage
C. Parquet offers row-based compression
D. Parquet files can only be used with Excel

Answer: B

NEW QUESTION # 114
Which techniques are commonly used to manage type conversion between SQL and Python when importing database values?
(Choose two)

A. Automatically casting Python variables to SQL column types without validation
B. Using a mapping function to convert SQL types into Python objects
C. Defining column types in Python using sqlite3.register_converter()
D. Ignoring data types and treating everything as strings

Answer: B,C

NEW QUESTION # 115
Which function is used to reshape a NumPy array without modifying the original data values?

A. reshape()
B. flatten()
C. transpose()
D. resize()

Answer: A

NEW QUESTION # 116
......

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