Certified Entry-Level Data Analyst with Python (PCED-30-0x)

Certified Entry-Level Data Analyst with Python (PCED) Exam Prep | Practice Questions and Detailed Explanations [2025]

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Certified Entry-Level Data Analyst with Python (PCED-30-0x)

Certified Entry-Level Data Analyst with Python (PCED-30-0x) udemy course

Certified Entry-Level Data Analyst with Python (PCED) Exam Prep | Practice Questions and Detailed Explanations [2025]

Certified Entry-Level Data Analyst with Python (PCED-30)

Course by CertCraft Institute

The Certified Entry-Level Data Analyst with Python (PCED-30) course from CertCraft Institute introduces learners to the fundamental tools and techniques used in data analysis with Python. This course prepares individuals for the PCED-30 certification by teaching essential programming, data handling, and visualization skills, helping learners understand how to work with real-world data and communicate insights effectively.

What You’ll Learn

  • Use Python to clean, transform, and organize data for analysis

  • Work with common data structures and libraries such as lists, dictionaries, NumPy, and pandas

  • Read data from files (CSV, Excel, JSON) and perform filtering, sorting, and grouping operations

  • Create basic data visualizations using matplotlib and seaborn

  • Apply statistical summaries and simple analysis techniques to interpret data

Requirements

  • Basic computer literacy and the ability to install and run software

  • Familiarity with Python fundamentals (variables, loops, functions) is helpful but not required

  • Access to a computer with Python and data analysis libraries (pandas, NumPy, matplotlib) installed

Who This Course Is For

  • Individuals preparing for the PCED-30 Data Analyst certification

  • Beginners interested in data analysis, reporting, or entry-level data roles

  • Students and recent graduates looking to build practical data handling skills

  • Career changers exploring data-related career paths with no prior experience

Topics Covered

  • Data Analysis Foundations – What data analysts do, common workflows, and toolsets

  • Python for Data Handling – Lists, dictionaries, loops, and working with built-in functions

  • Working with Files – Reading and writing data in CSV, Excel, and JSON formats

  • Using pandas and NumPy – DataFrames, arrays, indexing, filtering, and basic statistics

  • Data Visualization – Plotting data with matplotlib and seaborn for insights and communication

  • Basic Analysis Techniques – Descriptive statistics, sorting, grouping, and summarizing data