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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q79-Q84):

NEW QUESTION # 79
Which practices contribute to better exception handling in data pipelines involving file I/O and numerical computations?
(Choose two)

Answer: A,D


NEW QUESTION # 80
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: B


NEW QUESTION # 81
Which SQL command should a data analyst use to modify existing records in a database table based on specific conditions?

Answer: A


NEW QUESTION # 82
Which of the following libraries is specifically optimized for high-performance numerical computation with multi-dimensional arrays in Python?

Answer: D


NEW QUESTION # 83
Which of the following correctly demonstrates the use of parameterized queries using Python's sqlite3 module?

Answer: D


NEW QUESTION # 84
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