Data Handling and Visualization with Python
in Basics of Computing Language > PythonWhat you will learn?
In this module, you’ll learn how to work with data in Python—from importing, cleaning, and manipulating data to creating stunning visualizations that bring your data to life.
We start with data import and export, showing you how to load datasets from different sources. Then, we dive into data manipulation, where you’ll explore powerful tools like Pandas and Seaborn for wrangling, aggregating, and cleaning data efficiently.
You'll also learn to use Jupyter Notebooks to create clear and reproducible reports, making it easier to document and share your analysis.
The final section focuses on data visualization, where you’ll master plots like line charts, bar charts, scatter plots, histograms, box plots, heatmaps, and pair plots—including real-world examples with gene expression data. These skills will help you interpret trends, patterns, and relationships in your data effectively.
To make learning hands-on, you’ll have access to Google Colab notebooks for practicing each concept. Plus, quizzes at the end of each section will help reinforce what you’ve learned.
By the end of this module, you'll be confident in handling and visualizing data, setting a strong foundation for data analysis and machine learning.
