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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q133-Q138):

NEW QUESTION # 133
When working with relational databases in Python, what are key components required to establish and manage database connections?
(Choose all that apply)

Answer: C,D


NEW QUESTION # 134
Which of the following best describes the purpose of the plt.subplot() function in Matplotlib?

Answer: C


NEW QUESTION # 135
Which of the following are key differences between Pandas and NumPy arrays?
(Choose two)

Answer: A,B


NEW QUESTION # 136
You have a list of product prices, and you need to remove duplicate values while maintaining the fastest performance. Which core data structure should you use?

Answer: A


NEW QUESTION # 137
Which SQL command should a data analyst use to modify existing records in a database table based on specific conditions?

Answer: C


NEW QUESTION # 138
......

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