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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Python Programming for Data Analysis30%- Python Data Types and Structures
  • 1. Lists, tuples, dictionaries, sets
  • 2. Data type conversions
  • 3. Numbers, strings, booleans
- 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. Writing to files
  • 2. Reading from files (text, CSV)
  • 3. Context managers (with statement)
Topic 2: Data Analysis Fundamentals20%- 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
Topic 3: Applied Data Analysis Projects20%- Data Analysis Workflow
  • 1. Problem definition
  • 2. Results interpretation and presentation
  • 3. Data exploration and cleaning
  • 4. Analysis and modeling
- Exploratory Data Analysis (EDA)
  • 1. Data distribution analysis
  • 2. Pattern identification
  • 3. Descriptive statistics computation
  • 4. Correlation analysis
Topic 4: Working with Data Using Python Libraries30%- Data Visualization
  • 1. Matplotlib basics
  • 2. Seaborn introduction
  • 3. Customizing plots
  • 4. Creating basic charts (line, bar, scatter, histogram)
- NumPy Fundamentals
  • 1. Basic statistical functions
  • 2. NumPy arrays and operations
  • 3. Array indexing and slicing
  • 4. Vectorized operations
- Pandas Library
  • 1. GroupBy operations
  • 2. Data selection and filtering
  • 3. DataFrame operations (merge, join, concat)
  • 4. Handling missing data
  • 5. Series and DataFrame structures

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q81-Q86):

NEW QUESTION # 81
Which SQL clause is most appropriate when you need to filter records that meet a specific condition during data retrieval in an analytics pipeline?

Answer: C


NEW QUESTION # 82
What will the following function return?
def average(*args):
return sum(args) / len(args)
average(4, 5, 6)

Answer: B


NEW QUESTION # 83
What is the correct SQL statement to permanently remove a table named customers from a database?

Answer: C


NEW QUESTION # 84
What object-oriented principle allows a child class to reuse and extend the behavior of a parent class in a Python data modeling scenario?

Answer: A


NEW QUESTION # 85
Which method in the pandas library allows efficient loading of large datasets in chunks to conserve memory?

Answer: B


NEW QUESTION # 86
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