A self-contained, five-notebook path from basic Python syntax to object-oriented design, framed around behavioral-research examples, plus two written companions for setup and terminology.
Prerequisites: None — starts from zero
Estimated time: ~10–15 hours
After this module you can read and write Python for data work — variables, pandas/NumPy, plotting, comprehensions, and classes.
Reading guides in this module:
Guide 01 — Getting Started with Python (installation, environments, notebooks)
Guide 02 — Essential Python Terminologies and Concepts
Notebooks in this module:
| # | Notebook | What it covers |
|---|---|---|
| 01 | Data in Python - Foundation | Variables, data types, data structures, pandas, NumPy, operators |
| 02 | Data Automation | More pandas/NumPy, conditionals, loops, reusable functions |
| 03 | Data Visualization | matplotlib, seaborn, Plotly; distributions, time series, ethograms, publication-ready figures |
| 04 | Computational Thinking (DSA and Fluency) | Comprehensions, choosing data structures, Big-O intuition, algorithmic patterns, practice problems |
| 05 | Classes and Decorators | Object-oriented design, encapsulation, @property, @dataclass in a study data-management example |
All the required packages for this course are listed in the requirements.txt file. Please download it and keep it in the root directory of your project.