PCAD-31-02 Exam Test & PCAD-31-02 Pdf Format

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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Applied Data Analysis Projects20%- Exploratory Data Analysis (EDA)
  • 1. Descriptive statistics computation
  • 2. Pattern identification
  • 3. Data distribution analysis
  • 4. Correlation analysis
- Data Analysis Workflow
  • 1. Results interpretation and presentation
  • 2. Problem definition
  • 3. Analysis and modeling
  • 4. Data exploration and cleaning
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. Series and DataFrame structures
  • 3. Data selection and filtering
  • 4. Handling missing data
  • 5. GroupBy operations
- NumPy Fundamentals
  • 1. NumPy arrays and operations
  • 2. Array indexing and slicing
  • 3. Vectorized operations
  • 4. Basic statistical functions
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. Types of data (structured, unstructured, semi-structured)
  • 3. Data analysis concepts and terminology
Python Programming for Data Analysis30%- Control Flow and Functions
  • 1. Return values and scope
  • 2. Conditional statements (if, elif, else)
  • 3. Loops (for, while)
  • 4. Function definitions and parameters
- File Operations
  • 1. Reading from files (text, CSV)
  • 2. Writing to files
  • 3. Context managers (with statement)
- Python Data Types and Structures
  • 1. Lists, tuples, dictionaries, sets
  • 2. Numbers, strings, booleans
  • 3. Data type conversions

>> PCAD-31-02 Exam Test <<

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q43-Q48):

NEW QUESTION # 43
Which term best describes the process of combining customer data from multiple systems into a single unified dataset?

Answer: D


NEW QUESTION # 44
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: B


NEW QUESTION # 45
What is the primary purpose of using annotations in a data visualization?

Answer: D


NEW QUESTION # 46
Which characteristics are typically associated with supervised learning algorithms?
(Choose two)

Answer: B,C


NEW QUESTION # 47
Which of the following exceptions would most likely be raised if a string is directly converted to an integer in Python?

Answer: A


NEW QUESTION # 48
......

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