Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Latest Test Cram & PCAD-31-02 exam study guide & Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) detail study guides

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Python Institute PCAD-31-02 Exam Syllabus Topics:

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

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q39-Q44):

NEW QUESTION # 39
Which file formats are commonly used for hierarchical or nested data structures in data acquisition?
(Choose two)

Answer: C,D


NEW QUESTION # 40
What distinguishes structured data from unstructured data in the context of data modeling and storage?

Answer: C


NEW QUESTION # 41
Which of the following libraries is specifically optimized for high-performance numerical computation with multi-dimensional arrays in Python?

Answer: A


NEW QUESTION # 42
Which of the following practices contributes most to making Python scripts modular and maintainable?

Answer: A


NEW QUESTION # 43
Which practices contribute to better exception handling in data pipelines involving file I/O and numerical computations?
(Choose two)

Answer: A,B


NEW QUESTION # 44
......

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