In this course, we’ll explore how to visualize data using Python — with Matplotlib, Seaborn, and Pandas — all explained in Moroccan Darija.
If you’re learning data science, machine learning, or just want to make your data speak clearly, this is a core skill you must master.
Hey everyone,
After building strong foundations in Python, NumPy, and Pandas — I kept getting the same question:
“Okay, now how do I make graphs and understand data visually?”
So I put together this full course on data visualization — all in Darija — to walk you through everything from basic line plots to advanced heatmaps, histograms, and pair plots.
You’ll learn not only how to make visualizations, but when to use each type, and how to make them look professional and insightful.
What You’ll Learn
- Setup for Matplotlib and Seaborn
- Line Charts & Customizing Axes
- Titles, Labels, Legends & Styles
- Scatter Plots & Histograms (with multiple series)
- Bar Charts & Bar Plots with Averages
- Heatmaps, Pivot Tables, and Pair Plots
- Plotting from Pandas DataFrames
- Working with figure sizes, grids, and multiple charts
- Adding images and improving default styles
- Documentation tips and cheat sheets
This course is packed with practice and hands-on examples so you can use visualizations in real-world projects, not just academic demos.
Why I Made This
I noticed that a lot of beginner and intermediate learners don’t feel confident showing their results — even if their analysis is correct.
That’s where visuals come in — to tell stories, support arguments, and communicate clearly.
This course is for:
- Beginners in Data Science or ML
- Professionals who work with reports or dashboards
- Anyone who wants to turn boring numbers into visuals that speak for themselves
