Latest PCAD-31-02 Exam Papers | Certification PCAD-31-02 Exam

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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q68-Q73):

NEW QUESTION # 68
Which SQL commands can be used to modify the contents of a table's data directly?
(Choose all that apply)

Answer: A,D


NEW QUESTION # 69
Which data collection method is most appropriate when gathering opinions from a target audience at scale?

Answer: D


NEW QUESTION # 70
What is the benefit of using the __name__ == "__main__" construct in Python scripts?

Answer: D


NEW QUESTION # 71
Which operations are valid and commonly used on Python lists during data transformation tasks?
(Choose two)

Answer: A,C


NEW QUESTION # 72
What is the recommended Python library to connect and extract tabular data directly from an Excel file?

Answer: A


NEW QUESTION # 73
......

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