Manage Finance Data with Python & Pandas: Unique Masterclass (Udemy.com)
Analyze Stocks with Pandas, Numpy, Seaborn & ChatGPT. Create, analyze & optimize Index & Portfolios (CAPM, Alpha, Beta)
Created by: Alexander Hagmann
Last updated December 2025
What you will learn
- Step into the Financial Analyst role and give advice on a client´s financial Portfolio (Final Project)
- Import large Financial Datasets / historical Prices from Web Sources and analyze, aggregate and visualize them
- Calculate Return, Risk, Correlation and Rolling Statistics for Stocks, Indexes and Portfolios
- Create, analyze and optimize financial Portfolios and understand the use of the Sharpe Ratio
- Intuitively understand Modern Portfolio Theory (CAPM, Beta, Alpha, CML, SML, Risk Diversification) with Real Data examples
- Create Interactive Price Charts with Technical Indicators (Volume, OHLC, Candlestick, SMA etc.)
- Create Financial Indexes (price-, equal- and value- weighted) and understand the difference between Price Return and Total Return
- Easily switch between daily, weekly, monthly and annual returns and understand the benefits of log returns
How it compares
Against the other 388 rated Udemy courses in Python on CourseDuck:
- Rating4.3 out of 5higher than 25% of them
- Reviews1,166#172 of 389 by number of reviews
- Length29.9 hourslonger than 85% of them
- Last updatedDecember 2025more recently than 74% of them
Course Description
**Now with ChatGPT for Pandas & Data Analytics and Online Coding Exercises!**
The Finance and Investment Industry is experiencing a dramatic change driven by ever-increasing processing power & connectivity and the introduction of powerful Machine Learning tools. The Finance and Investment Industry is more and more shifting from a math/formula-based business to a data-driven business.
What can you do to keep pace?
No matter if you want to dive deep into Machine Learning, or if you simply want to increase productivity at work when handling Financial Data, there is the very first and most important step: Leave Excel behind and manage your Financial Data with Python and Pandas!
Pandas is the Excel for Python and learning Pandas from scratch is almost as easy as learning Excel. Pandas seems to be more complex at a first glance, as it simply offers so much more functionalities. The workflows you are used to do with Excel can be done with Pandas more efficiently. Pandas is a high-level coding library where all the hardcore coding stuff with dozens of coding lines are running automatically in the background. Pandas operations are typically done in one line of code! However, it is important to learn and master Pandas in a way that
you understand what is going on
you are aware of the pitfalls (Don´ts)
you know best practices (Dos)
MANAGE FINANCE DATA WITH PYTHON & PANDAS best prepares you to master new challenges and to stay ahead of your peers, fellows and competitors! Coding with Python/Pandas is one of the most in-demand skills in Finance.
This course is one of the most practical courses on Udemy with 200 Coding Exercises and a Final Project. You are free to select your individual level of difficulty. If you have no experience with Pandas at all, Part 1 will teach you all the essentials (From Zero to Hero).
Part 2 - The Core of this Course
Import Financial Data from Free Web Sources, Excel- and CSV-Files
Calculate Risk, Return, and Correlation of Stocks, Indexes and Portfolios
Calculate simple Returns, log Returns, and annualized Returns & Risk
Create your own customized Financial Index (price-weighted vs. equal-weighted vs. value-weighted)
Understand the difference between Price Return and Total Return
Create, analyze and optimize Stock Portfolios
Calculate Sharpe Ratio, Systematic Risk, Unsystematic Risk, Beta and Alpha for Stocks, Indexes and Portfolios
Understand Modern Portfolio Theory, Risk Diversification and the Capital Asset Pricing Model (CAPM)
Forward-looking Mean-Variance Optimization (MVO) and its pitfalls
Get an exclusive insight into how MVO is used in Real World (and why it is NOT used in many cases) -> get beyond Investments 101 level!
Calculate Rolling Statistics (e.g. Simple Moving Averages) and aggregate, visualize and report Financial Performance
Create Interactive Charts with Technical Indicators (SMA, Candle Stick, Bollinger Bands etc.)
Part 3 - Capstone Project
Step into the Financial Analyst / Advisor Role and give advice on a Client´s Portfolio (Final Project Challenge).
Apply and master what you have learned before!
Part 4
Some advanced topics on handling Time Series Data with Pandas.
Appendix
Do you struggle with some basic Python / Numpy concepts? Here is all you need to know if you are completely new to Python!
Why you should listen to me...
In my career, I have built an extensive level of expertise and experience in both areas: Finance and Coding
Finance:
10 years experience in the Finance and Investment Industry...
...where I held various quantitative & strategic positions.
MSc in Finance
Passed all three CFA Exams (currently no active member of the CFA Institute)
Python & Pandas:
I led a company-wide transformation from Excel to Python/Pandas
Code, models, and workflows are Real World Project-proven
Instructor of the highest-rated and most trending general Course on Pandas
What are you waiting for? Guaranteed Satisfaction: Otherwise, get your money back with a 30-Days-Money-Back-Guarantee.
Looking Forward to seeing you in the Course!
Instructor Details
- 4.3 Rating
1,166 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 Bogdan on 4/13/2026
Great course for start. I value practice and finance oriented environment. Good for aspiring financial analysts and data analysts. There are several disadvantages such as slightly slow pace and outdated functions.
By Ilja Buerkle on 1/24/2026
Sehr guter und informativer Kurs im Bereich Finanzanalyse und Pandas. Das Pensum war in Ordnung. Die Sprache ist klar und deutlich. Kleines Minus: Die Interaktiven Workshops waren nicht verfügbar. Trotzdem gab es viele Praxisbeispiele und Übungen. Alles in Allem ein Top-Kurs
By Anonymized User on 8/27/2024
I'm halfway through the course and it has met my expectations. I have some experience with python and pandas before starting. Some beginners may be challenged on making code current. For example, this plt.style.use("seaborn") should be plt.style.use("seaborn-v0_8")
By Kiran Laxman Thombare on 8/23/2024
It's really interesting and comprehensive course. Due small duration videos, it's easy to learn while doing my other works.
By Hynek Kyvala on 6/18/2024
The course materials are easy to follow, up-to-date, and well-organized. A significant portion of the course covers Python and Pandas. Although I had some prior knowledge, it served as a great refresher and I even learned some new things, especially when applying the learned knowledge to financial data analysis.
By Michal Safar on 3/15/2024
This course is made by very knowledgeable person, that probably works with pandas very often. Some here presented information I have not found in any other course. However, for me personally, the talks was king of lifeless and I found it very hard to keep focused. Some videos I had to replay because I found myself thinking about other stuff.
By Lim Kang Wei on 6/12/2022
There's a lot of fundamental financial theories covered before every code demonstrated. I like the plotly and cufflinks part, it's cool
By Cincy Wang on 3/17/2021
So far I feel this tutorial class is very helpful. The instructor explains everything step by step, and I have a clear vision about each coding line. I will leave some feedbacks after finishing more courses.
By FVC on 7/28/2020
This is an exceptional guide on how to use Python in financial data analysis. Alexander clearly understands the topics at hand and gives numerous examples on how to calculate different metrics (return, risk, correlations, portfolio optimization, etc.) and how to access data and create and customize charts. This is one of the best courses I have taken in Udemy.
By Richie Narr on 1/4/2020
Pros:- The course went into great depth to explain how different functions and modules can be used in Python. Therefore, it was useful. Cons:- 1. Some videos are to long. Video length should be restricted to an average of around 5 to 6 minutes per video. 2. Some of the functions and how the function has produced the output should be explained more clearly.
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 86 / 100









