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Python Institute PCAD-31-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: SQL and Database Integration10%- Relational database concepts
  • 1. Tables, keys, relationships and normalization
- Python-database connectivity
  • 1. Executing queries and retrieving results
  • 2. Connecting to SQLite, MySQL or PostgreSQL
  • 3. Error handling and best practices
- SQL querying
  • 1. SELECT, WHERE, JOIN, GROUP BY, aggregate functions
  • 2. Subqueries and filtering
Topic 2: Data Modeling and Machine Learning Basics20%- Supervised learning fundamentals
  • 1. Classification: logistic regression, k-NN, decision trees
  • 2. Model training, testing and evaluation
  • 3. Regression: linear, multiple, polynomial
- Model performance and optimization
  • 1. Accuracy, precision, recall, F1-score
  • 2. Overfitting, underfitting and generalization
  • 3. Hyperparameter tuning basics
Topic 3: Data Visualization and Communication15%- Visualization principles and best practices
  • 1. Choosing appropriate chart types
  • 2. Audience-focused presentation
  • 3. Color, layout and clarity
- Visualization with Matplotlib and Seaborn
  • 1. Line, bar, scatter, histogram, box plots
  • 2. Customization and styling
  • 3. Heatmaps, pair plots and correlation matrices
- Data storytelling and reporting
  • 1. Structuring insights and conclusions
  • 2. Written and verbal presentation techniques
Topic 4: Data Acquisition and Preprocessing30%- Data preparation with Pandas and NumPy
  • 1. Data structures: Series, DataFrame, ndarray
  • 2. Data reshaping and aggregation
  • 3. Indexing, filtering, sorting and grouping
- Data cleaning and validation
  • 1. Quality assurance and validation techniques
  • 2. Data standardization and transformation
  • 3. Handling missing, duplicate and invalid values
- Data collection, integration and storage
  • 1. Data collection methods and sources
  • 2. Data formats and storage systems
  • 3. Data integration and merging
Topic 5: 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. Identifying patterns, trends and outliers
  • 2. Feature selection and dimensionality reduction basics
- Descriptive statistics
  • 1. Measures of central tendency and dispersion
  • 2. Correlation and covariance analysis
  • 3. Frequency distributions and percentiles

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

1. Which operation would most efficiently apply element-wise multiplication to two NumPy arrays of equal size?

A) array1 * array2
B) numpy.matrix()
C) array1.dot(array2)
D) numpy.outer()


2. When performing bootstrapping on a dataset with 500 observations, what is a typical procedure?

A) Creating samples by removing all duplicates
B) Scaling all values between 0 and 1 before resampling
C) Drawing one sample and calculating the mean only once
D) Generating multiple datasets of the same size by randomly sampling with replacement


3. Which operations are recommended when organizing messy tabular data in Pandas for further transformation and statistical modeling?
(choose two)

A) Converting the DataFrame to a Series
B) Ensuring consistent data types
C) Dropping column headers
D) Resetting the index after filtering


4. Why is it important to manage object identity correctly in complex data analysis pipelines?

A) It guarantees consistent hashing of string values
B) It avoids redundant copies and preserves shared state when required
C) It ensures type casting is consistently applied
D) It prevents reloading modules unnecessarily


5. Which technique is considered a primary defense against SQL injection when executing database queries from Python?

A) Escaping quotes manually in SQL strings
B) Using parameterized queries
C) Closing the database cursor after each query
D) Encrypting the database connection


Solutions:

Question # 1
Answer: A
Question # 2
Answer: D
Question # 3
Answer: B,D
Question # 4
Answer: B
Question # 5
Answer: B

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