In this course, we’ll learn how to explore and analyze real datasets using Python — all explained in Moroccan Darija.
This is where your data skills become insights — preparing you for real-world analysis, reports, and dashboards.
Hey everyone,
After helping many people get started with Python, Pandas, and Data Visualization, it was time to take the next big step:
How do you go from raw data to real insights?
That’s what Exploratory Data Analysis (EDA) is about. It’s one of the most important steps in any data science or business intelligence workflow.
So I created this project-based, code-heavy course — completely in Darija — to walk you through a real exploratory analysis from start to finish.
What You’ll Learn
Exploratory Data Analysis – Project
- Where to find datasets for analysis
- Setting up your environment properly
- Understanding and cleaning your dataset
- Extracting meaningful patterns and insights
- Writing custom functions to automate aggregation
- Visualizing your findings with custom figure grids
- Exporting your final results and charts
Exploratory Data Analysis – Project
We analyze a real dataset from HCP Morocco and Kaggle:
- Country & age distributions
- Education and employment types
- Programming languages and learning methods
- Creating dynamic reports from data
- Presenting findings with confidence
Why I Made This
I’ve worked with people who had never written a line of code — yet they had mountains of data sitting unused.
Data doesn’t speak until someone asks the right questions.
In this course, you’ll see how to:
- Make messy datasets usable
- Extract high-quality insights
- Communicate results like a true data analyst
Whether you’re preparing for your first data science role, building dashboards, or just want to understand data like a pro, this course is for you.
