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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q135-Q140):

NEW QUESTION # 135
Which SQL clause is most appropriate when you need to filter records that meet a specific condition during data retrieval in an analytics pipeline?

A. WHERE
B. GROUP BY
C. HAVING
D. ORDER BY

Answer: A

NEW QUESTION # 136
When working with relational databases in Python, what are key components required to establish and manage database connections?
(Choose all that apply)

A. Cursor object for executing queries
B. Python's random module for generating keys
C. Connection object to interface with the database
D. Database driver or module (e.g., sqlite3)

Answer: C,D

NEW QUESTION # 137
Which packages are most commonly used together in a data science workflow for data manipulation and visualization?
(Choose two)

A. NumPy
B. flask
C. pandas
D. Pygame

Answer: A,C

NEW QUESTION # 138
Which SQL commands are typically used to retrieve and manipulate data in a data analysis context?
(Choose all that apply)
Response:

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

Answer: A,C

NEW QUESTION # 139
Which approaches are commonly used to extract structured data from APIs in Python?
(Choose two)

A. Use the requests module to retrieve JSON responses
B. Access data using requests.get() and parse it with .json()
C. Open Excel files using matplotlib
D. Load CSV directly with re.compile()

Answer: A,B

NEW QUESTION # 140
......

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