Python Institute PCED-30-02 Exam Details & Actual Exam Questions

  • Exam Code/Number: PCED-30-02
  • Exam Name/Title: PCED - Certified Entry-Level Data Analyst with Python
  • Certification Provider: Python Institute
  • Corresponding Certification: Python Institute PCED
  • Exam Questions: 52
  • Updated On: Jul,17 2026
  • Certification Level: Entry / Foundational

Python Institute PCED - Certified Entry-Level Data Analyst with Python Exam Questions

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Python Institute PCED-30-02 Exam Overview:

Certification Vendor:Python Institute (OpenEDG)
Exam Name:PCED™ – Certified Entry-Level Data Analyst with Python
Exam Number:PCED-30-02
Exam Price:USD 69
Real Exam Qty:40
Exam Format:Single-select questions, Multiple-select questions
Exam Duration:60 minutes
Related Certifications:PCEP™ – Certified Entry-Level Python Programmer
PCAP™ – Certified Associate in Python Programming
Available Languages:English, Spanish
Passing Score:70%
Certificate Validity Period:Lifetime
Sample Questions:Python Institute PCED-30-02 Sample Questions
Exam Way:Online proctored exam via OpenEDG TestNow™ platform
Pre Condition:No formal prerequisites; basic familiarity with Python or programming recommended
Official Syllabus URL:https://pythoninstitute.org/pced-exam-syllabus

Python Institute PCED-30-02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Introduction to Data and Data Analysis Concepts22.5%- 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 types and measurement scales
  • 1. Qualitative vs quantitative data
  • 2. Nominal, ordinal, interval, ratio scales
- Data lifecycle and ethical considerations
  • 1. Privacy, security, bias, and fairness in data
  • 2. Data collection, storage, processing, usage, and sharing
- Basic statistical concepts
  • 1. Population, sample, variable, observation
  • 2. Descriptive vs inferential statistics
Topic 2: 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. Lists, tuples, sets, dictionaries
  • 2. Variables, numbers, strings, booleans
- Control flow and functions
  • 1. Basic exception handling
  • 2. Defining and calling functions, parameters, return values
  • 3. Conditional statements, loops, iteration
- Introduction to NumPy
  • 1. Arrays, basic operations, indexing, slicing
Topic 3: Data Visualization and Communication20%- Principles of effective data visualization
  • 1. Choosing appropriate chart types
  • 2. Clarity, simplicity, and accuracy
- 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 4: Working with Data and Performing Simple Analysis25%- Data cleaning and preparation
  • 1. Formatting and standardizing values
  • 2. Filtering, sorting, transforming data
  • 3. Handling missing values, duplicates, and errors
- 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. Reading text, CSV, and structured files
  • 2. Importing data from external sources


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