Programming & Web Development
Python for Data Science
Put Python to work on real data.
3 daysIntermediate10 modulesPCED: Certified Entry-Level Data Analyst with Python
About this course
Put Python to work on real data. Over three days you will set up Anaconda and Jupyter, compute with NumPy arrays, clean, filter and reshape data with pandas, read from Excel, CSV, SQL databases and APIs, handle missing values and group operations, and visualise results with Matplotlib and Seaborn in an end-to-end project.
Curriculum
10 modules
- Overview of Python and its role in data science
- Setting up Python environments (Anaconda, Jupyter Notebooks)
- Writing and running Python scripts
- Introduction to Jupyter Notebooks
- Markdown and code cells
- Running, saving, and sharing notebooks
- Understanding arrays and their advantages
- Creating and manipulating NumPy arrays
- Mathematical operations and broadcasting
- Understanding Series and DataFrames
- Importing and exploring datasets
- Filtering, sorting, and transforming data
- Reading and writing Excel files
- Working with CSV files
- Connecting and querying SQL databases
- Transforming structured and unstructured data
- Importing datasets from APIs and web sources
- Altering specific data using custom functions
- Handling missing data - filling, dropping, and imputing values
- Aggregating data using group operations
- Creating fully customizable plots
- Implementing custom figures and axis
- Adding labels, legends, and annotations
- Creating scatter plots
- Generating distribution plots
- Visualizing summary statistics with box plots
- Data analysis case studies
- End-to-end data science project
- Best practices for working with large datasets
Who it's for
Analysts and developers with basic Python who want to explore, prepare and visualise data.
Before you start
- To be successful in this course, learners should have the level of knowledge and experience gained from Introduction to Python
Prepares for
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