The Complete Pandas Bootcamp 2025: Data Science with Python (Udemy.com)
Now with ChatGPT for Pandas, Online Exercises, Seaborn, Machine Learning. Fully Updated (Pandas 3.x) as of Sep 2024
Created by: Alexander Hagmann
Last updated December 2025
What you will learn
- Bring your Data Handling & Data Analysis skills to an outstanding level.
- Learn and practice all relevant Pandas methods and workflows with Real-World Datasets
- Learn Pandas based on NEW Version 2.x (already anticipating 3.x)
- Import, clean, and merge messy Data and prepare Data for Machine Learning
- Master a complete Machine Learning Project A-Z with Pandas, Scikit-Learn, and Seaborn
- Analyze, visualize, and understand your Data with Pandas, Matplotlib, and Seaborn
- Practice and master your Pandas skills with Quizzes, 150+ Exercises, and Comprehensive Projects
- Import Financial/Stock Data from Web Sources and analyze them with Pandas
- Learn and master the most important Pandas workflows for Finance
- Learn the Basics of Pandas and Numpy Coding (Appendix)
- Learn and master important Statistical Concepts with scipy
Course Description
**Now with ChatGPT for Pandas and more than 20 Udemy Online Coding Exercises - NEW Feature**
Welcome to the web´s most comprehensive Pandas Bootcamp. This is the only Pandas course you´ll ever need:
most comprehensive course with 36+ hours of video content
new AI features like Pandas Coding and Advanced Data Analysis with ChatGPT
150+ Coding Exercises (Online and Offline Exercises)
Practical Case Studies for Data Scientists and Finance Professionals
Fully updated to Pandas 2.2 and already anticipating Pandas 3.x
This course has one goal: Bringing your data handling skills to the next level to build your career in Data Science, Machine Learning, Finance & co. It has five parts:
Pandas Basics - from Zero to Hero (Part 1).
The complete data workflow A-Z with Pandas: Importing, Cleaning, Merging, Aggregating, and Preparing Data for Machine Learning. (Part 2)
Two Comprehensive Project Challenges that are frequently used in Data Science job recruiting/assessment centers: Test your skills! (Part 3).
Application 1: Pandas for Finance, Investing and other Time Series Data (Part 4)
Application 2: Machine Learning with Pandas and scikit-learn (Part 5)
Why should you learn Pandas?
The world is getting more and more data-driven. Data Scientists are gaining ground with $100k+ salaries. It´s time to switch from soapbox cars (spreadsheet software like Excel) to High Tuned Racing Cars (Pandas)!
Python is a great platform/environment for Data Science with powerful Tools for Science, Statistics, Finance, and Machine Learning. The Pandas Library is the Heart of Python Data Science. Pandas enables you to import, clean, join/merge/concatenate, manipulate, and deeply understand your Data and finally prepare/process Data for further Statistical Analysis, Machine Learning, or Data Presentation. In reality, all of these tasks require a high proficiency in Pandas! Data Scientists typically spend up to 85% of their time manipulating Data in Pandas.
Can you start right now?
A frequently asked question of Python Beginners is: "Do I need to become an expert in Python coding before I can start working with Pandas?"
The clear answer is: "No! Do you need to become a Microsoft Software Developer before you can start with Excel? Probably not!"
You require some Python Basics like data types, simple operations/operators, lists and numpy arrays. In the Appendix of this course, you can find a Python crash course. This Python Introduction is tailor-made and sufficient for Data Science purposes!
In addition, this course covers fundamental statistical concepts (coding with scipy).
In Summary, if you primarily want to use Python for Data Science or as a replacement for Excel, this course is a perfect match!
Why should you take this Course?
It is the most relevant and comprehensive course on Pandas.
It is the most up-to-date course and the first that covers Pandas Version 2.x. The Pandas Library has experienced massive improvements in the last couple of months. Working with and relying on outdated code can be painful.
Pandas isn´t an isolated tool. It is used together with other Libraries: Matplotlib and Seaborn for Data Visualization | Numpy, Scipy and Scikit-Learn for Machine Learning, scientific, and statistical computing. This course covers all these Libraries.
ChatGPT for Pandas Coding and advanced Data Analytics included!
In real-world projects, coding and the business side of things are equally important. This is probably the only Pandas course that teaches both: in-depth Pandas Coding and Big-Picture Thinking.
It serves as a Pandas Encyclopedia covering all relevant methods, attributes, and workflows for real-world projects. If you have problems with any method or workflow, you will most likely get help and find a solution in this course.
It shows and explains the full real-world Data Workflow A-Z: Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Explanatory Data Analysis through to preparing and processing data for Statistics, Machine Learning, Finance, and Data Presentation.
It explains Pandas Coding on real Data and real-world Problems. No toy data! This is the best way to learn and understand Pandas.
It gives you plenty of opportunities to practice and code on your own. Learning by doing. In the exercises, you can select the level of difficulty with optional hints and guidance/instruction.
Pandas is a very powerful tool. But it also has pitfalls that can lead to unintended and undiscovered errors in your data. This course also focuses on commonly made mistakes and errors and teaches you, what you should not do.
Guaranteed Satisfaction: Otherwise, get your money back with a 30-Days-Money-Back-Guarantee.
I am looking forward to seeing you in the course!
Instructor Details
- 4.8 Rating
3,892 Reviews
Alexander Hagmann
Alexander is a Data Scientist and Finance Professional with more than 10 years of experience in the Finance and Investment Industry.
He is a Bestselling Udemy Instructor for
- Algorithmic Trading
- Data Analysis/Manipulation with Pandas
- (Financial) Data Science
- Python for Business and Finance
- ChatGPT and other AI tools
Alexander started his career in the traditional Finance sector and moved step-by-step into Data-driven and Artificial Intelligence-driven Finance roles. He is currently working on cutting-edge Fintech projects and creates solutions for Algorithmic Trading and Robo Investing. And Alexander is excited to share his knowledge with others here on Udemy. Students who completed his courses work in the largest and most popular tech and finance companies all over the world.
Alexander´s courses have one thing in common: Content and concepts are practical and real-world proven. The clear focus is on acquiring skills and understanding concepts rather than memorizing things.
Alexander holds a Master´s degree in Finance and passed all three CFA Exams (he is currently no active member of the CFA Institute).
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Reviews
By Thomas Byrne on 4/18/2026
Your explanation of the basics was superb. You cleared up a lot of topics which caused confusion to me. That was first class. i found myself saying out loud. Ah, so that's how that works. Unfortunately for me, who is not a seasoned python/pandas user, i found the code quite tricky at times. I felt there was an expectation that the reader was of a certain level, which is not the case for me. I am a newbe when it comes to coding and i now feel i need to go and find a slightly easier course which will promote me to the level of your course. Many thanks for your time & effort in preparing what was a truly comprehensive & educational course. Tom
By Pratik Dave on 5/31/2023
This is a fantastic course for learners not familiar with python and would like to develop foundation knowledge with practical examples. It gradually moves from beginner to advanced/intermediate level of data science concepts. I wish lessons and exercises will be continuously updated so learners can come back and update their knowledge as and when required.
By Barbara Gladfelter on 12/1/2022
I'm almost finished with this course, but even though I'm on to other projects I keep coming back to this course if I'm unsure of something. That's because it is the most complete and thorough course on pandas I've found. Alex doesn't miss a detail. If you want to be proficient in pandas, this the place to be.
By Z A on 9/30/2022
Pretty solid. Alexander is super thorough in the mega videos he provides. You might have to google some things to broaden you're understanding or provide more context but what more do you want when trying to learn on your own. The only thing I might suggest Alexander is more practice problems or perhaps something most effective would be Section Assignments for each section. Overall great course, looking forward to trying a few of the other ones you've produced. Thanks!
By Congyi Wei on 9/30/2022
I will always take Alex's courses. He is responsible, patient and kind to students' questions. His courses are comprehensive and detailed. If students find something being repeated, it is important to know that studying is a repetitive process. Something important are repeated throughout the course, so students could remember them well. This is a common-known fact in pedagogical practice. Courses of Alex are very thorough and contents are more than good for the price, almost angelic.
By Kiefer Edwards on 4/4/2021
I took course this during the start of the COVID shut down, I was out of work and not in school. I've had some experience using python for computational programming but no experience with pandas or data analysis, but this course fixed that. It contains just about everything you need to get started and be proficient in data analysis. If the other students couldn't answer a question, Alexander always responded in a timely manner; so you'll always get the help you need. I'm currently referring back to this course as a reference for current analysis work I'm doing for an advanced physics lab, and this helps tremendously; to really understand stuff, jump to the importing section and find your own data you're curious about, and you'll truly see how amazing this course is! Over a year later he's still updating the course and you still have access!
By Bhanurdra Narayan Mohapatra on 2/23/2020
Thanks Alex for such a great course. This is the best course for anyone like to learn Pandas. I can sense that you have brought the do's and don't's from your real life work experience. The course is curated such a way anyone can learn. Anyone wants to learn Machine Learning, this is the starting point. Only thing I would like to some Videos regarding handling of Json, databases, except that it is perfect. Thanks Alex for such great course !!
By YuanYuan Olsen on 12/25/2019
Hi Alex, this is an amazing tutorial on not only Pandas but all related areas that are fundamentals essential to data science. A very good introduction to data science yet deep enough that allows one to start on any project at a heartbeat. I also appreciate the lesson structure in a short no more than 12 min segments to psychologically grab and engage students' attention, the style that builds the dynamics step by step from ease to difficulty and the numerous repetition that shows the application of the concepts/building blocks and serves to students' memory retention. Can't say enough about this course and will definitely come back to revisit for refreshing and reference. Thank you so much! Ava Olsen
By Steve M on 9/25/2019
This course covers much of the functionality in Pandas. It's packed full of examples and quizzes along the way to sharpen your skills and help retain the information. I felt the pace of the course was right on target, as one lesson is built upon the next. The author spoke clearly and concisely and I'd recommend this course to anyone looking to learn Pandas.
By Nikolaos A. Mitsiou on 4/7/2019
Fantastic course! The instructor is very meticulous and explains everything in a very detailed and constructive fashion. I've read the Wes Mckinney's book on Data Analysis with Python (creator of the pandas library) and Alexander is covering most of the topics. Also, the fact that there are lots of hands-on opportunities makes this course stand out from the competition.
Quality Score
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Overall Score : 96 / 100








