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Python for Finance: Financial Analysis for Investing

Use Python to Find Good Investments. Learn Pandas, NumPy, Matplotlib for Financial Analysis & Automate Value Investing.
(465 reviews)
6,224 students
Created by


CourseMarks Score®







Platform: Udemy
Video: 21h 14m
Language: English
Next start: On Demand

Top Financial Analysis courses:

Detailed Analysis

CourseMarks Score®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 5/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.4 / 10
We analyzed factors such as the rating (4.5/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.8 / 10
Video Score: 10.0 / 10
The course includes 21h 14m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 4 hours 25 minutes of 111 Financial Analysis courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
6 resources.
0 exercise.
0 test.

Table of contents


Did you know that the No.1 killer of investment return is emotion?
Investors should not let fear or greed control their decisions.
How do you get your emotions out of your investment decisions?
A simple way is to perform objective financial analysis and automate it with Python!
•Performing financial analysis makes your decisions objective – you are not buying companies that your analysis did not recommend.
•Automating them with Python ensures that you do not compromise because you get tired of analyzing.
•Finally, it ensures that you get all the calculation done correctly in the same way.
Does this sound interesting?
•Do you want to learn how to use Python for financial analysis?
•Find stocks to invest in and evaluate whether they are underpriced or overvalued?
•Buy and sell at the right time?
This course will teach you how to use Python to automate the process of financial analysis on multiple companies simultaneously and evaluate how much they are worth (the intrinsic value).
You will get started in the financial investment world and use data science on financial data.

Why should you enroll in this course?
•Over 3,000 students have signed up within the first week of the course going live!
•Making investment decisions is like playing poker without looking at your cards if you don’t know what you are doing.
•You don’t want to buy stocks in a company you did not analyze first.
•This is the only course that takes you through the full process from finding attractive investments and how to time your first buy.
•Similarly, you do not buy a house without looking at the condition report.
•How to see if a company will grow in value, to avoid falling stock prices the day after you buy it.
•This course does not assume you have a portfolio and want to optimize it – it will help you find the stocks to invest in first.
•It gives you a solid foundation to invest with confidence and stop gambling.
•Learn that making financial analysis on companies is not that difficult and can be automated with Python.
•The market crashed in 2020 without any warning – some companies came in quickly, others did not.
•Be sure to invest in companies with a solid economy and a growth market.

Early reviews
“Excellent course, everything is brilliantly explained, step by step with exercices, practical example and it seems that further on the course it will be real world example. I’m about 25% in the course, it was so exciting that I encouraged one of my friend to signup in the course. I already followed all other Rune’s great courses, and this one, for me is the best among them. Also, in every Rune’s course, he answer quickly for all single question with detail, this one followed the rules. For me it’s one of the best instructors here on Udemy, I have enrolled in many other best instructors course here, and Rune is definitely one of them.” – Adel
“Accurate and very detailed” – Moshe
“good course!” – Richard
“Starting good… can’t wait for more.” – Swietopelk
“Really engaging instructor.” – Edwin

How is this course structured?
•This course will guide you through how to install the necessary software (Anaconda) – it’s all free.
•It will cover how to use Jupyter Notebook (from Anaconda package) if you are not completely familiar with it.
•A crash course in Python if you need an update or come from a different programming background.
•Then it starts by introducing financial concepts along with Python programming to fully understand them.
•This includes understanding of stocks, volume, dividends, returns, market price, price to earnings (EPS), price to earnings (PE ratio), book value and more.
•A deep introduction to Pandas, the most important library used for financial analysis with Python.
•It will cover DataFrames, Series, read and write data, export to Excel, merge, join and link data and much more.
•The concept of intrinsic value (a fair stock price to pay) – this is the most important concept to understand when investing.
•How the risk of investment is understood and how to assess it for a company.
•This is how the management of a company is assessed in an objective way.
•This will include learning about debt-to-equity ratio (DE ratio), current assets, return of investment (ROI), revenue evaluation, earnings per share (EPS) evaluation, book value evaluation, free-cash-flow (FCF) evaluation and more.
•This teaches you how to calculate a fair price (intrinsic value) to be paid for a company.
•Matplotlib is introduced and how it can be used to visualize data for efficient data interpretation.
•We visualize data and export it to color-formatted Excel sheets – all from Python.
•You will learn to use free APIs to read up-to-date data on stock quotes and financial statements.
•Then we dive deeper and work with historical time series data on stock prices.
•This teaches you rate of return, percentage change, and normalization.
•How to calculate and use the Compound Annual Growth Rate (CAGR).
•There will be a case study on DOW theory.
•Next, we will examine and calculate technical indicators such as moving averages (MA), MACD, stochastic oscillator and RSI, and how to use them to buy and sell.
•We introduce NumPy to perform further analyzes.
•This will help us calculate and understand the volatility of a stock.
•Also, correlation between stocks, linear regression, beta, CAPM, and more.
•How to work with a full portfolio.
•This includes concepts like Sharpe ratio, Monte Carlo Simulation, Efficient Frontier and more.

This course has
•21 hours of video in 180+ lectures.
•Exercises are prepared in Jupyter Notebooks.
•Links to useful resources along the way.
•Explains all concepts in an easy way with real examples.

Udemy has a refund guarantee with a 30 day money back guarantee that ensures if you are not satisfied, you will get your money back. Also, feel free to contact me directly if you have any questions.

About the instructor
Rune is a Ph.D. in computer science with a background in Python programming. He has taken an MBA from Henley Business School in the UK to study business administration and economics. Rune has been teaching programming and computer science since college. He has other best-selling courses at Udemy.

You will learn

✓ How to automate financial analysis with Python using Pandas and Numpy
✓ Learn to find attractive companies to invest in using fundamental analysis with Pandas
✓ Identify when to buy and sell stocks based on technical analysis using Pandas and Numpy
✓ Export your financial analysis to Excel in formatted multi sheets
✓ How to calculate a fair price (intrinsic value) of a stock with Python using Pandas
✓ Introduction to Pandas, Numpy and Visualization of financial data
✓ Use Monte Carlo simulation to optimize your portfolio allocation
✓ Understand risk when buying stock shares
✓ Learn how to evaluate an investment to lower the risk
✓ Learn about Intrinsic value, Market value, Book value, and Shares
✓ Master the concepts Dividend, Earnings per share (EPS), Price/Earnings (PE) ratio, and Volume Yield
✓ Cover a Python Crash Course with all the basic Python
✓ How to use DataFrames for financial analysis
✓ Use Matplotlib to visualize DataFrames with time series data
✓ How to join, merge and concatenate DataFrame
✓ Export data from Python to Excel in nice colorful sheets with charts
✓ Calculate concrete intrinsic values (a fair price to buy a stock for) for 50 companies
✓ Read and interpret Dept/Equity (DE) ratio, Current ratio, Return of Investment (ROI) and more
✓ Use revenue, Earnings-per-share (EPS), and Book value to determine if a company is predictable and worth investing in.
✓ How to use Price/Earnings (PE) ratio to make calculations
✓ How to use Pandas Datareader to read data directly form API of financial pages
✓ To read financial statements from API’s
✓ Web scraping of pages and how to convert data to correct format and types
✓ How to calculate rate of return (RoR), percentage change, and to normalize stock price data
✓ Understand and learn to calculate the CAGR (Compound Annual Growth Rate)
✓ A deep dive case study of DOW theory
✓ How to calculate technical indicators, like, Moving Average (MA), MACD, Stochastic Oscillator, and more
✓ Make financial calculations with NumPy
✓ Calculate with vectors and matrices using NumPy
✓ How to calculate the Volatility of a stock
✓ Correlation and Linear Regression between securities between investments
✓ How the Beta is used and how to calculate it
✓ Deep dive into using CAPM
✓ Optimize your portfolio of investments
✓ Learn what Sharpe Ratio is and how to use it
✓ How to use Monte Carlo Simulation to simulate random variables
✓ Use Sharpe Ratio and Monte Carlo Simulation to calculate the Efficient Frontier
✓ Advice on next books to read about investing


• Some knowledge of programming is recommended
• All software and data used in course is free
• Ability to install Anaconda (guide in course)

This course is for

• Someone that wants to learn about financial analysis with Python
• Anyone that wants to start data science on financial data
• Programmers that want to learn about finance and investing

How much does the Python for Finance: Financial Analysis for Investing course cost? Is it worth it?

The course costs $14.99. And currently there is a 82% discount on the original price of the course, which was $84.99. So you save $70 if you enroll the course now.
The average price is $19.2 of 111 Financial Analysis courses. So this course is 22% cheaper than the average Financial Analysis course on Udemy.

Does the Python for Finance: Financial Analysis for Investing course have a money back guarantee or refund policy?

YES, Python for Finance: Financial Analysis for Investing has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Python for Finance: Financial Analysis for Investing course, but there is a $70 discount from the original price ($84.99). So the current price is just $14.99.

Who is the instructor? Is Rune Thomsen a SCAM or a TRUSTED instructor?

Rune Thomsen has created 7 courses that got 1,307 reviews which are generally positive. Rune Thomsen has taught 41,833 students and received a 4.5 average review out of 1,307 reviews. Depending on the information available, Rune Thomsen is a TRUSTED instructor.
Computer Science, PhD/CS, MBA
Hi, I’m Rune.
Thank you for checking my course.
With a PhD in Computer Science, an MBA to learn business administration and finance, 10+ years in professional software development, I still find my greatest passion in teaching.
I have helped students succeed with programming since I took my PhD in computer science and was teaching at Aarhus University, Denmark.
Since then, I was a software engineer (programmer), the head of branch of developers, build big software solutions, and software engineering manager in a software as a service (SaaS) company.
Along that journey, I took an MBA from Henley Business School in UK to learn about business administration and finance.

My journey on Udemy started in 2020 and the focus has been on Python programming, which is my greatest passion. I love to make concepts easy to understand and fun to learn.
Until now I have the Udemy Bestseller:
Master Modern Security and Cryptography by Coding in Python

I started to program as 12 years old before the internet was available for common people (read: for me).
It was Basic, yes the language Basic with line numbers.
My best friend started and we helped each other to get better. Before I reached college, I had helped many friends with programming.
It was natural for me to teach at college and I missed it when I left after teaching all the fundamental programming and computer theory courses at least once.
Later I have helped new employees to program, as well as other professionals to automate their work with Python.
I have helped a guy with no experience in programming to get his first job within 6 months of starting.

If anything, please feel free to reach out to me and I’ll be there for you every step of the way.
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CourseMarks Score®







Platform: Udemy
Video: 21h 14m
Language: English
Next start: On Demand

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