Are you tired of feeling anxious and uncertain when paying your bills or buying new things?
Do you constantly worry about not having enough money to go on sunny vacations and enjoy a wonderful life?
The truth is, if you don't take action to improve your financial literacy and skillset, you are setting yourself up for a future of even more stress and struggle.
Stuck in a dead-end job with no hope of advancement, you feel trapped and frustrated, unable to achieve your goals to live your dream life.
It's time to stop feeling trapped and frustrated and take your financial future into your own hands.
Learning the skill of financial analysis through Python can help you do just that.
With this skill, you'll be able to make informed investment decisions and understand the financial performance of businesses, giving you the knowledge you need to make the most of your money.
Since the demand for individuals with financial analysis and investing skills is at an all-time high, companies worldwide are searching for experts in this field. Without individuals possessing these skills, businesses struggle to make informed financial decisions and risk falling behind their competitors.
By mastering Python for Finance, you'll be able to provide essential expertise to these companies and secure a profitable and fulfilling career in the process.
Hi, I am Rune
Rune, a Ph.D. in computer science with a background in Python programming and an MBA from Henley Business School, has helped over 50,000 students on Udemy learn this valuable skill.
His course, "Python for Finance: Financial Analysis for Investing," teaches you the most straightforward and fastest way to create data models that can analyze large amounts of financial data in seconds, giving you the insights you need to make better and faster financial decisions.
With Rune's help, you can bypass all the unnecessary knowledge that other courses and schools teach. You will learn the things you actually need, which will make the process a whole lot simpler.
"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 Rune one of the best instructors."
For many people, this dream seems impossible, and they continue to struggle with financial data year after year. They try different software, take finance courses, and hire consultants, but nothing seems to work.
There's a better way, and Rune is here to show you how. He has seen many businesses struggle with financial data and has helped them to overcome these struggles through the power of Python programming.
In his course, he shows you the struggles businesses face when trying to make sense of financial data and how traditional methods fall short. You will see that it's not just you but that businesses around the world are facing the same issues.
After acquiring this knowledge, businesses will rely on you to help make better financial decisions while also earning an excellent income for yourself.
It's time to stop struggling with finance and start making progress toward your financial goals. With Rune's help, you can finally achieve financial freedom and impact the world.
With lifetime access to over 21 hours of video in 180+ lectures, real-world examples and exercises, and links to valuable resources, you'll gain a comprehensive understanding of basic Python concepts to advanced financial models and analysis techniques in no time.
Enroll now for just $197 and take the first step towards achieving your financial freedom. Plus, with our 30-day money-back guarantee, you have nothing to lose.
Don't let the fear of financial uncertainty hold you back. Take action now and start learning Python for Finance.
With Rune's expert guidance and the excellent "Python for Finance: Financial Analysis for Investing" course, you'll have everything you need to achieve financial freedom and secure a stable future for yourself and your loved ones.
But time is of the essence. Without the right knowledge and skills, you could miss out on opportunities to grow your money and live a comfortable life.
Don't let that happen to you. Enroll in "Python for Finance: Financial Analysis for Investing" today and take control of your financial future.
- Introduction (0:55)
- Jupyter Notebook Cheat Sheet
- Jupyter Notebook: The Dashboard (3:23)
- Jupyter Notebook: Run and restart a Notebook (3:04)
- Jupyter Notebook: Coppy and Reorganize Code (2:01)
- Jupyter Notebook: Comments and Markdowns (2:21)
- Jupyter Notebook: Tab + Tab + Shift & Tab (6:14)
- What did we learn? (0:54)
- Introduction (1:07)
- Variables and Types (11:43)
- Print statement (2:53)
- Boolean expressions (6:16)
- If-statements (5:04)
- Python Lists (5:19)
- For-loops (4:38)
- While-loops (2:32)
- Python Dictionaries (dict) (4:05)
- Other data types (3:45)
- Python Functions (4:20)
- Lambda Functions (7:41)
- Exercises (5:07)
- Solutions (12:49)
- New to Python? We have all been there. (3:15)
- What did we learn? (1:13)
- Introduction (1:19)
- Intrinsic Value (3:35)
- Introduction to the Lemonade Stand (5:28)
- The Lemonade Stand - the easy to understand example (5:01)
- Jupyter Notebook: The Lemonade Stand (15:58)
- Shares (4:35)
- Shares a story - Understand what they really are (6:08)
- Jupyter Notebook: Shares (13:05)
- Dividend (4:16)
- Dividend a story - an easy way to understand dividend (5:36)
- Jupyter Notebook: Dividend (14:13)
- What did we learn? (2:30)
- Introduction (6:21)
- Introduction to Pandas - a small demonstration (11:13)
- Series (12:07)
- DataFrames - Part I (12:09)
- DataFrames - Part II (7:13)
- DataFrames - Part III (7:55)
- DataFrames - Part IV (7:14)
- DataFrames - Part V (7:39)
- Read and Write with Pandas - Part I (11:24)
- Read and Write with Pandas - Part II (10:56)
- Read and Write with Pandas - Part III (10:41)
- Merge - Join - Concat - Part I (8:46)
- Merge - Join - Concatenate - Part II (5:04)
- Transpose and Clean (7:38)
- Views (5:47)
- Useful methods (8:33)
- Apply - An awesome method to master (6:09)
- Exercises (5:19)
- Solutions (10:42)
- What did we learn? (2:07)
- Introduction (1:13)
- Outcome of section (6:52)
- Understand Risk - Part I (4:20)
- Understand Risk - Part II (3:08)
- Understand Risk - Part III (2:58)
- Understand Risk - All put together (2:39)
- Evaluate Leadership (9:37)
- Debt to Equity ratio - Evaluation (4:21)
- Jupyter Notebook: Dept-to-equity ratio (19:34)
- Current ratio - Evaluation (3:25)
- Jupyter Notebook: Current ratio (10:34)
- Stable and predictable (8:06)
- Return of Investment (ROI) - Evaluation (5:04)
- Jupyter Notebook: Return of Investment (9:39)
- Revenue - Evaluation (4:38)
- Jupyter Notebook: Revenue (16:48)
- Earnings Per Share (EPS) - Evaluation (2:04)
- Jupyter Notebook: Earnings Per Share (EPS) (9:01)
- Book Value - Evaluation (3:52)
- Jupyter Notebook: Book Value (11:43)
- Free Cash Flow (FCF) - Evaluation (1:48)
- Jupyter Notebook: Free Cash Flow (FCF) (4:49)
- Combine all data (3:11)
- Jupyter Notebook: Combine all data (10:46)
- Calculate a Fair Price (Intrinsic Value) (6:50)
- Price-to_earnings (PE) ratio (2:38)
- Jupyter Notebook: Price-to-Earnings (PE) ratio (5:32)
- Jupyter Notebook: Calculate a Fair Price (Intrinsic Value) (10:27)
- Compare it with Current Price (9:38)
- What did we learn? (4:29)
- Introduction (0:57)
- Overview of Section (5:06)
- Jupyter Notebook: Matplotlib basics (8:58)
- Jupyter Notebook: Work with Axis (9:04)
- Jupyter Notebook: Title and Labels (9:07)
- Jupyter Notebook: Matplotlib and pandas (8:04)
- Jupyter Notebook: pandas and data structures (11:42)
- Jupyter Notebokk: Bar plots (10:00)
- Exercises (5:35)
- Solutions (14:47)
- What did we learn? (1:25)
- Introduction (0:55)
- What will we learn? (3:08)
- Pandas Datareader - Remote Data Access (1:37)
- Jupyter Notebook: Pandas Datareader - Part I (18:27)
- Jupyter Notebook: Pandas Datareader - Part II (9:28)
- Yahoo! Finance API - read Financial Statements (2:34)
- Jupyter Nobtebook: Yahoo! Finance API (13:11)
- Web Scraping (2:43)
- Jupyter Notebook: Web Scraping (15:35)
- Exercises (3:50)
- Solutions (11:45)
- What did we learn? (1:08)
- Introduction (3:34)
- Rate of Return, Percentage Change, and Normalization (5:55)
- Jupyter Notebook: Rate of Return, Percentage Change, and Normalization (10:19)
- CAGR (2:02)
- Jupyter Notebook: CAGR (8:30)
- Jupyter Notebook: Multiple Time Frames (7:46)
- Case Study: DOW Theory (15:26)
- Jupyter Notebook: Case Study: DOW Theory (14:28)
- What did we learn? (1:19)
- Introduction (2:36)
- What is a Technical Indicator and Types of Indicators (7:09)
- Indicator: Moving Average (5:02)
- Jupyter Notebook: Simple Moving Average (MA) (14:31)
- Jupyter Notebook: Exponential Moving Average (EMA) (7:26)
- Indicator: MACD (4:25)
- Jupyter Notebook: MACD (11:56)
- Indicator: Stochastic Oscillator (3:47)
- Jupyter Notebook: Stochastic Oscillator (12:46)
- Jupyter Notebook: Exporting to Excel (17:27)
- Jupyter Notebook: Using our Excel Sheet (10:27)
- Exercises (6:03)
- Solutions (11:02)
- What did we learn? (0:50)
- Introduction (5:48)
- Jupyter Notebook: Introduction to NumPy (13:17)
- Jupyter Notebook: Index, Slicing, and Views (10:35)
- Jupyter Notebook: DataFrames and Series with NumPy (13:51)
- Jupyter Notebook: Vectorization with NumPy (10:46)
- Jupyter Notebook: Matplotlib and NumPy (9:23)
- Jupyter Notebook: Dot product and Transpose (11:36)
- Exercises (6:31)
- Solutions (11:08)
- What did we learn? (2:13)
- Introduction (1:30)
- Adjusted Close (2:20)
- Volatility of a Stock (5:13)
- Jupyter Notebook: Volatility Calculations (20:00)
- Correlation Between Securities (2:11)
- Jupyter Notebook: Correlation Calculations (7:54)
- Linear Regression (3:29)
- Jupyter Notebook: Linear Regression (14:13)
- Beta Calculations (2:05)
- Jupyter Notebook: Beta Calculations (8:58)
- CAPM (4:14)
- Jupyter Notebook: CAPM Calculations (8:00)
- Exercises (4:00)
- Solutions (8:32)
- What did we learn? (1:47)
- Introduction (1:28)
- Portfolios (1:21)
- Jupyter Notebook: Portfolio (10:40)
- Sharpe Ratio (2:38)
- Jupyter Notebook: Sharpe Ratio Calculations (11:05)
- Monte Carlo Simulations (3:45)
- Jupyter Notebook: Monte Carlo Simulations - Introduction (13:45)
- Jupyter Notebook: Portfolios and Monte Carlo Simulations (13:58)
- Jupyter Notebook: The Efficient Frontier (4:49)
- Exercises (4:35)
- Solutions (13:33)
- What did we learn? (1:28)
Python for Finance
How to automate financial analysis with Python using pandas and NumPy
"I was new to Python when I started this course, but was drawn to it because of how efficiently data could be collected and organized inside of Jupyter notebook. This was a great course taught by an awesome teacher who teaches about basic investment principles and how to perform these calculations inside of Jupyter notebook. This is a great class and you won't regret enrolling in it. The teacher also does a great job of answering questions." - Alexandra
"One of the best courses I've ever taken, and I've taken a lot. Thanks Rune for this course. My confidence has tripled now, especially when I start applying for Quantitative Data scientist roles this year." - Jason O.
"Excellent course for anyone trying to learn coding and investing." - Lorenzo B.
"I really like the exercises. I'm fairly new to Python and when I attempted the exercises on my own some of my code was different but the charts looked the same. I guess there are more then one way to do it. I'm learning a lot and loving it!!!" - Nate H.
"Prof. Rune is very passionate about the subject, he's charismatic as well and makes it fun with his sense of humour, great guy." - Hiba Y.
"the course is so resourceful for beginners and Rune is a great instructor, he replies every time i ask i will start to go deeper in portfolio management, python. i hope Rune makes an advanced course on Portfolio management" - Rayan A.
"Amazing course, i got a lot of knowledge about financial analysis and great skills with python to automate all the processes. Thanks Rune for your work and for what i learned from you!! Absolutely adviced." - Federico B.
"Rune's explanations of complex topics are surprisingly simple. Also, he's enthusiasm make the course more fun. I've taken a few course on Python for Finance and I can say this is the best one by far. Thank you, Rune!" - Isis Nize G.
"Very good combination of Python and Financial Analysis. My favorite course so far. Thank you." - Marek K.
"The instructor is very capable and will answer your questions immediately. You should take this course now." - 鈴木佳子
"Dr. Rune is one of the best instructor I have met in my life. It is great course and great instructor" - Hadwan L.
"Comprehensive and practical instruction on stock analysis. I am familiar with programming. But have not used Python before. The introductory Python lesson was enough to grasp the coding in later sections. The methods taught in this course will save hours of research and trial and error. I can highly recommend this course to anyone wanting to develop their own stock analysis engine." - Patrick D.
"If you have thought about investing or even analyzing investment strategies and have no idea where to start; this course answers those questions." - Shawn H.
"Lectures are very clear, they are in technical professional English with on topic. Provides all the resources and specific instructions. Great course to follow. Thank you" - Sirisena
"An excellent course. Although I have no previous experience in finance, Rune explained everything very well. It was very important for me that he answered the questions I asked quickly. Thanks for this nice course." - Ayhan C. I.
"I didn't expect to get all these practical well elaborated explanations. I'm loving this though still trying to grasp since I'm new to python never ever used it before. So far, good content with value." - Donald J. O.
"Rune is very entertaining which helps on reasonable dry subjects such as financial analysis." - Michael C.
I am student in Quantitative Finance and this course is perfectly balanced between theory and practice. Rune has a deep and sincere passion for the subject and keeps you glued to the screen! Thank you!" - Alberto B.