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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Python Programming for Data Analysis30%- Python Data Types and Structures
  • 1. Lists, tuples, dictionaries, sets
  • 2. Numbers, strings, booleans
  • 3. Data type conversions
- Control Flow and Functions
  • 1. Conditional statements (if, elif, else)
  • 2. Function definitions and parameters
  • 3. Return values and scope
  • 4. Loops (for, while)
- File Operations
  • 1. Context managers (with statement)
  • 2. Reading from files (text, CSV)
  • 3. Writing to files
Data Analysis Fundamentals20%- Introduction to Data Analysis
  • 1. Types of data (structured, unstructured, semi-structured)
  • 2. Data analysis process lifecycle
  • 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
Applied Data Analysis Projects20%- Exploratory Data Analysis (EDA)
  • 1. Correlation analysis
  • 2. Pattern identification
  • 3. Data distribution analysis
  • 4. Descriptive statistics computation
- Data Analysis Workflow
  • 1. Analysis and modeling
  • 2. Problem definition
  • 3. Results interpretation and presentation
  • 4. Data exploration and cleaning
Working with Data Using Python Libraries30%- Data Visualization
  • 1. Creating basic charts (line, bar, scatter, histogram)
  • 2. Seaborn introduction
  • 3. Matplotlib basics
  • 4. Customizing plots
- NumPy Fundamentals
  • 1. Array indexing and slicing
  • 2. Vectorized operations
  • 3. Basic statistical functions
  • 4. NumPy arrays and operations
- Pandas Library
  • 1. Handling missing data
  • 2. Data selection and filtering
  • 3. Series and DataFrame structures
  • 4. DataFrame operations (merge, join, concat)
  • 5. GroupBy operations

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q119-Q124):

NEW QUESTION # 119
Which practices help ensure secure and effective execution of SQL queries in Python scripts?
(Choose all that apply)

Answer: A,D


NEW QUESTION # 120
Which of the following exceptions would most likely be raised if a string is directly converted to an integer in Python?

Answer: B


NEW QUESTION # 121
What is the primary goal of pre-processing data before performing analysis?

Answer: C


NEW QUESTION # 122
Which techniques are commonly used to manage type conversion between SQL and Python when importing database values?
(Choose two)

Answer: C,D


NEW QUESTION # 123
What is the main purpose of using the bootstrapping technique in inferential statistics?

Answer: D


NEW QUESTION # 124
......

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