Python Institute PCED - Certified Entry-Level Data Analyst with Python PCED-30-02 Certified Exam Dumps

PCED-30-02 Exam Dumps

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Certification Provider: Python Institute
Exam Code / Number: PCED-30-02
Exam Name: PCED - Certified Entry-Level Data Analyst with Python
Exam Questions: 52
Last Updated: Jun 23, 2026
Corresponding Certification: Python Institute PCED

Go To PCED-30-02 Questions

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Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Python Basics for Data Analysis32.5%- Built-in modules for data work
  • 1. math, statistics, datetime, collections, csv
- Core Python syntax and data types
  • 1. Variables, numbers, strings, booleans
  • 2. Lists, tuples, sets, dictionaries
- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
- Control flow and functions
  • 1. Conditional statements, loops, iteration
  • 2. Defining and calling functions, parameters, return values
  • 3. Basic exception handling
Topic 2: Data Visualization and Communication20%- Principles of effective data visualization
  • 1. Clarity, simplicity, and accuracy
  • 2. Choosing appropriate chart types
- Creating basic visualizations
  • 1. Line charts, bar charts, histograms, pie charts
  • 2. Using text and simple plotting tools
- Interpreting and presenting results
  • 1. Deriving conclusions and insights
  • 2. Reporting findings clearly and concisely
Topic 3: Working with Data and Performing Simple Analysis25%- Data aggregation and grouping
  • 1. Summarizing and grouping datasets
- Exploratory data analysis
  • 1. Identifying patterns, trends, and outliers
  • 2. Calculating mean, median, mode, range, variance, standard deviation
- Data acquisition and loading
  • 1. Importing data from external sources
  • 2. Reading text, CSV, and structured files
- Data cleaning and preparation
  • 1. Filtering, sorting, transforming data
  • 2. Handling missing values, duplicates, and errors
  • 3. Formatting and standardizing values
Topic 4: Introduction to Data and Data Analysis Concepts22.5%- Data types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
- Basic statistical concepts
  • 1. Population, sample, variable, observation
  • 2. Descriptive vs inferential statistics
- Definition and classification of data
  • 1. Role of data in decision-making and business
  • 2. Process of turning raw data into insights
  • 3. Difference between data, information, and knowledge
- Data lifecycle and ethical considerations
  • 1. Privacy, security, bias, and fairness in data
  • 2. Data collection, storage, processing, usage, and sharing


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