PCAD-31-02 Certification Test Questions | PCAD-31-02 Free Exam Dumps

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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Data Visualization and Communication15%- Visualization with Matplotlib and Seaborn
  • 1. Customization and styling
  • 2. Line, bar, scatter, histogram, box plots
  • 3. Heatmaps, pair plots and correlation matrices
- Data storytelling and reporting
  • 1. Structuring insights and conclusions
  • 2. Written and verbal presentation techniques
- Visualization principles and best practices
  • 1. Color, layout and clarity
  • 2. Audience-focused presentation
  • 3. Choosing appropriate chart types
Data Acquisition and Preprocessing30%- Data preparation with Pandas and NumPy
  • 1. Indexing, filtering, sorting and grouping
  • 2. Data reshaping and aggregation
  • 3. Data structures: Series, DataFrame, ndarray
- Data collection, integration and storage
  • 1. Data collection methods and sources
  • 2. Data formats and storage systems
  • 3. Data integration and merging
- Data cleaning and validation
  • 1. Data standardization and transformation
  • 2. Handling missing, duplicate and invalid values
  • 3. Quality assurance and validation techniques
Data Modeling and Machine Learning Basics20%- Supervised learning fundamentals
  • 1. Regression: linear, multiple, polynomial
  • 2. Classification: logistic regression, k-NN, decision trees
  • 3. Model training, testing and evaluation
- Model performance and optimization
  • 1. Accuracy, precision, recall, F1-score
  • 2. Overfitting, underfitting and generalization
  • 3. Hyperparameter tuning basics
SQL and Database Integration10%- Relational database concepts
  • 1. Tables, keys, relationships and normalization
- SQL querying
  • 1. Subqueries and filtering
  • 2. SELECT, WHERE, JOIN, GROUP BY, aggregate functions
- Python-database connectivity
  • 1. Connecting to SQLite, MySQL or PostgreSQL
  • 2. Error handling and best practices
  • 3. Executing queries and retrieving results
Data Exploration and Statistical Analysis25%- Inferential statistics
  • 1. Statistical significance and interpretation
  • 2. Hypothesis testing and confidence intervals
  • 3. Probability concepts and distributions
- Exploratory data analysis
  • 1. Feature selection and dimensionality reduction basics
  • 2. Identifying patterns, trends and outliers
- Descriptive statistics
  • 1. Measures of central tendency and dispersion
  • 2. Frequency distributions and percentiles
  • 3. Correlation and covariance analysis

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Python Institute Certified Associate Data Analyst with Python (PCAD-31-02) Sample Questions (Q42-Q47):

NEW QUESTION # 42
Which of the following exceptions would most likely be raised if a string is directly converted to an integer in Python?

Answer: D


NEW QUESTION # 43
Which metric is most appropriate for evaluating the accuracy of a classification model?

Answer: A


NEW QUESTION # 44
When working with relational databases in Python, what are key components required to establish and manage database connections?
(Choose all that apply)

Answer: B,C


NEW QUESTION # 45
Which of the following statements best describes the structural relationship between Pandas Series and DataFrames?

Answer: D


NEW QUESTION # 46
What may occur if a model is evaluated using the same data it was trained on?

Answer: D


NEW QUESTION # 47
......

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