Data Analysis with Python: PCED Exam Preparation
Turn raw data into clear answers using Python.
About this course
Turn raw data into clear answers using Python. Over five days you will follow the full analysis lifecycle: collecting data from files, databases and APIs, cleaning and preparing it, then exploring it with pandas and NumPy.
You will calculate and interpret key statistics, try simple modelling, and present your findings with charts that a non-technical audience can understand. The course also covers responsible data handling, follows the published PCED content outline and prepares you for the Certified Entry-Level Data Analyst with Python exam.
What you'll learn
- Describe the data analysis lifecycle and the role of the data analyst
- Acquire data from files, databases and simple APIs
- Clean and prepare data by handling missing values, duplicates and outliers
- Explore and summarise data with pandas and NumPy
- Calculate and interpret descriptive statistics and correlations
- Communicate findings with clear, well-chosen visualisations
- Apply ethical and responsible practices when handling data
Curriculum
- The role of the data analyst
- Types and sources of data
- The data analysis lifecycle
- Ethics, privacy and responsible data use
- Core Python refresher for analysts
- Lists and dictionaries as data structures
- Functions and modules
- Working in Jupyter notebooks
- Reading CSV, Excel and JSON files
- Introduction to relational databases
- Basic SQL queries
- Collecting data from web APIs
- Handling missing values and duplicates
- Data types and conversions
- Detecting and treating outliers
- Transforming and standardising data
- NumPy arrays and vectorised operations
- pandas Series and DataFrames
- Selecting, filtering and sorting
- Grouping and aggregation
- Merging and reshaping data
- Measures of central tendency and spread
- Distributions
- Correlation
- Basic probability and sampling
- Framing analytical questions
- Exploring patterns and trends
- Introduction to simple linear regression
- Interpreting and validating results
- Charts with Matplotlib and Seaborn
- Choosing the right chart
- Telling a story with data
- Presenting findings to non-technical audiences
- PCED exam structure and question types
- Timed practice questions
- Reviewing weak areas
- Test-day preparation
Who it's for
Beginners and professionals with basic Python who want to start a career in data analysis and earn the PCED certification.
Before you start
- Basic Python knowledge, equivalent to the PCEP level
- Comfort with basic spreadsheet work and arithmetic
Prepares for
Part of these Alalamia diplomas
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