This guide is for anyone who wants to use Python to analyze data, whether to outgrow spreadsheets or as a base for machine learning. Every option is on Udemy, and I read every fact on the course page.
- Best overall: Boris Paskhaver's Data Analysis with Pandas and Python, 17.5 hours updated in July 2026.
- For analysts and business intelligence: Maven Analytics' NumPy & Pandas Masterclass, 13.5 hours.
- Most in-depth: Alexander Hagmann's Complete Pandas Bootcamp, 37 hours with exercises, Seaborn and an intro to machine learning.
| Course | Level | Length | View course |
|---|---|---|---|
| Data Analysis with Pandas and Python [2026] Udemy Best overall | All levels | 17.5 h | View course |
| Python Data Analysis: NumPy & Pandas Masterclass Udemy For analysts | All levels | 13.5 h | View course |
| The Complete Pandas Bootcamp 2025: Data Science with Python Udemy Most in-depth | All levels | 37 h | View course |
What you need to learn
Data analysis in Python almost always follows the same path, and each step has a main library:
- Load: read CSV files, spreadsheets or database tables into a pandas DataFrame.
- Clean: deal with missing values, duplicates and wrong types.
- Transform: filter, group and join tables with pandas. NumPy sits underneath and does the array math.
- Analyze: compute averages, counts and comparisons between groups.
- Visualize: turn the result into charts with Matplotlib or Seaborn.
I favored courses that make you run that path several times on real datasets. A lesson that only explains each function teaches you less.
Boris Paskhaver: best overall
Data Analysis with Pandas and Python [2026]
Boris Paskhaver • Udemy
17.5 hours focused on pandas, updated on July 28, 2026, with about 26,700 reviews and a 4.7 rating. For people who want to get fluent in the library they will use every day.
- Level
- All levels
- Length
- 17.5 h
- Certificate
- Completion
- Rating
- 4.7 (27k)
- Audio
- English
- Subtitles
- English; 27 more languages
Pros
- 17.5 hours focused on pandas, updated July 28, 2026
- 4.7 rating from about 26,700 reviews
Cons
- Centered on pandas: charts and machine learning are not the focus
The course stays on pandas: loading, cleaning and reshaping data. Charts and machine learning get little time, so if you need visualizations early, add a plotting tutorial.
Maven Analytics: for analysts and business intelligence
Python Data Analysis: NumPy & Pandas Masterclass
Maven Analytics, Chris Bruehl • Udemy
13.5 hours on NumPy and pandas from Chris Bruehl, aimed at data analysis and business intelligence. A good fit for analysts moving from spreadsheets to Python.
- Level
- All levels
- Length
- 13.5 h
- Certificate
- Completion
- Rating
- 4.6 (2.9k)
- Audio
- English
- Subtitles
- English; 5 more languages
Pros
- 13.5 hours on NumPy and pandas, updated June 29, 2026
- Aimed at data analysis and business intelligence work
Cons
- About 2,900 reviews, far fewer than Paskhaver's course
It was updated on June 29, 2026. It is the shortest course here and the only one with NumPy in the title. It has about 2,900 reviews, far fewer than Paskhaver's.
Alexander Hagmann: most in-depth
The Complete Pandas Bootcamp 2025: Data Science with Python
Alexander Hagmann • Udemy
37 hours with online exercises, Seaborn charts and an introduction to machine learning. For people who want one long course that goes from pandas to their first models.
- Level
- All levels
- Length
- 37 h
- Certificate
- Completion
- Rating
- 4.7 (3.9k)
- Audio
- English
- Subtitles
- 3 languages
Pros
- 37 hours, the longest pandas course in this comparison
- Online exercises, Seaborn charts and an introduction to machine learning
- Updated December 29, 2025
Cons
- Long if you only need the pandas basics
It was updated on December 29, 2025 and has about 3,900 reviews with a 4.7 rating. The length is the trade-off: if you only need the basics, Paskhaver's course gets you there in half the time.
How I chose
I used the same methodology as every guide. For this topic I looked at four things: hands-on work with real data, coverage of pandas and NumPy, recent updates and entry level. For now I only compare courses on Udemy. I read every fact on the course page on September 28, 2026.
I left out Jose Portilla's Python for Data Science and Machine Learning Bootcamp. It has more than 160,000 reviews, but it has not been updated since May 2020. I also left out Brandyn Ewanek's Python Data Analysis Bootcamp, which is marked intermediate and has about 120 reviews.
Frequently asked questions
Do I need to know Python first?
Basic Python helps with all three. If you have never programmed, spend a few days on Python syntax before starting a pandas course.
What is the difference between NumPy and pandas?
NumPy works with arrays of numbers and fast math. pandas uses NumPy underneath and organizes data in tables (DataFrames) with named columns, which makes filtering, grouping and joining easier.
Is Python for data a good base for machine learning?
Yes. Loading and cleaning data with pandas is the first step of almost every machine learning project. See also the guide to machine learning courses for beginners.
Do I need to install anything?
The courses use Python with libraries such as pandas and NumPy, which are open source. Each course explains how to set up the environment in its first section.