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Python for Data Science: Complete Bootcamp

Master Python programming for data science. From basics to advanced data analysis with NumPy, Pandas, Matplotlib, and Seaborn. Real-world datasets and projects.

ID: 1003
4.7
(891)
5,000 Students Enrolled
3 Hours
5 Lessons
Arabic

Instructor: Prof. Omar Farouk

What You Will Learn

Write clean, efficient Python code for data analysis
Manipulate and analyze data with NumPy and Pandas
Create stunning visualizations with Matplotlib and Seaborn
Clean and prepare real-world messy datasets
Apply statistical concepts to draw meaningful insights from data

Who This Course Is For

Complete beginners who want to learn Python for data analysis
Business analysts looking to automate their data workflows
Students in science, engineering, or economics who work with data
Professionals seeking to transition into a data science career

Prerequisites

No programming experience required — we start from scratch
A computer with internet access (Windows, Mac, or Linux)
Basic math skills (high school level is sufficient)
Willingness to practice coding exercises daily

Course Content

This Course Includes

3 Hours
5 Lessons
Arabic
Completion Certificate

Instructor

Prof. Omar Farouk

Prof. Omar Farouk

Professor of Data Science at Cairo University. Published researcher in machine learning and artificial intelligence.

Student Reviews

4.0
3 Reviews
5
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4
1
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Hassan Mahmoud

Hassan Mahmoud

July 15, 2025

Prof. Omar is a brilliant teacher. The way he breaks down NumPy and Pandas makes even the complex operations feel simple. The real-world dataset exercises were the highlight.

Instructor

Thank you Hassan! Your progress has been remarkable. Looking forward to seeing you in the ML course.

Tariq Nasser

Tariq Nasser

August 8, 2025

Very informative course. As a high school teacher, I appreciate how well-structured it is. The data cleaning exercise was challenging but rewarding.

Karim Bouazizi

Karim Bouazizi

September 1, 2025

Decent course but the pacing felt a bit fast for a beginner-level course. Some concepts like broadcasting in NumPy needed more time. The Pandas coverage is excellent though.