Ever since I started this Python for Finance series on The Babylonians in 2020, many have asked me questions on how I learn python. Since there is a demand for it, I have dedicated an entire post for those who are keen to learn. I would be sharing the exact same steps I took and consolidate all my resources to learn python for finance. Hopefully, this can give you a headstart or perhaps an inspiration.
This particular post would be continuously updated as and when there are new learning materials which I found useful. So do check back once in a while for new updates.
Looking back at the past month, I am actually quite surprised at my own progress. I would never have imagined myself writing all these codes and doing stock analysis or technical analysis using python. At least not within one month. But this really goes to show how easy it is to pick up this language. And If I can pick it up, I am sure anyone else could do it also.
Prior Background Knowledge
As mentioned in my earlier post, I graduated with a degree in accountancy knowing nothing about computer science and programming. But I have dabbled with CodeAcademy and FreeCodeCamp, just for a while before giving up.
Then I went to Bogazici University in Istanbul to take C programming & History of Modern Middle East, hence the great interest in Netflix’s new show: Rise of Empires: Ottoman. Anyways, got a C- or something for my C programming. That is as far as my experience or knowledge in programming goes, a C student. So I am really not that far off from anyone else.
When I made the decision to learn python for finance in 2020, I have no idea where to start either. So I just went to Udemy and searched “Python for Finance”. The word “for Finance” was deliberate. That is because I want to make sure I am learning python in the context of finance and not just a general python course. But that has changed now.
Since it was the first week of 2020, there was a promotion going on for Udemy courses. So I just bought all the bestseller and top-rated Udemy courses that came out in the search results. I think I got around four of five courses, but I refunded some. That is the good thing about Udemy. They allow a refund within 30 days if you are not satisfied with the course.
Most of the things that I have posted about Python for Finance is a variation of the lessons and examples that were covered in these courses. So it is really nothing impressive as many would have thought. If you followed the exact same path as me, I am sure you would have also replicated similar results, or even better.
A Beginner’s Journey Towards Learning Python
For those that have absolutely zero knowledge about programming and have never even written a single line of code, then I would suggest you start off gentle. Just go to places like CodeAcademy and familiarise yourself with all the syntax and logic first before jumping to Udemy.
Most programming languages follow the same concepts. You just have to learn basic things like operators, variables boolean expressions, while loops, for loops, conditional statements and etc. Then you have a foundation to work with. For those that are like me, know a little but actually know nothing, the best way to learn would be getting your hands dirty by doing python projects.
Giles McMullen-Klein describes it quite accurately. Learning python and learning the syntax is not difficult. The hard part comes from thinking computationally and algorithmically to solve problems. You can know what variable is and how loops work, but yet don’t know how to write codes to solve a problem. That is because those are two very different skill sets. It is good to keep that in mind while learning python.
Udemy Courses That I Bought: (*Affiliate links)
1. Python for Finance: Investment Fundamentals & Data Analytics (Week 1)
2. Python for Financial Analysis and Algorithmic Trading (Week 2) *Refunded
3. Manage Finance Data with Python & Pandas: Unique Masterclass (Week 3)
4. Importing Financial Data with Python from Free Web Sources (Week 4)
5. The Complete Python Programmer Bootcamp 2020 (Week 5) *Refunded
6. Web Scraping with Python: BeautifulSoup, Requests & Selenium (Week 7)
All these courses that I have outlined are all the top-rated and best-seller courses in Udemy. I refunded the second one because it gets too technical especially during the Quantopian trading section. But the first part of his course is really good.
The last one is taught by Giles McMullen-Klein. His videos are very different from others. It teaches you to think computationally and solve problems. His capstone project even teaches you to write a code in python to detect coin shapes and count the change.
Unfortunately, there are incomplete videos and some of them got cut halfway. It is still not fixed yet, so I refunded as I am still within 30 days. But if it’s resolved at the point in time when you read this, then I would highly recommend it. If not, just watch his YouTube videos. His channel name is Python Programmer.
If you are interested in the Udemy courses, just wait until it is < $20 before you buy them. NEVER buy them when it is $29.99 or even worse $209.99. Just be patient and wait for a promo. They do all sorts of discounts and promotions every time, especially if it’s your first time on Udemy. And remember, you always have the option to refund a course within 30 days. I have tried it and it works seamlessly.
Recommended Youtube Channels to Follow:
1. Corey Schafer (He is the BEST Python Youtuber I know so far)
2. Python Programmer (He is quite solid also, the guy that stresses computational thinking)
3. Sentdex (He is quite good also, self-employed since 12. Learnt everything on his own)
4. Data School (General Python tutorials – Pandas, syntax and etc.)
Do watch some of them to get a good sense of why python? Introduction to python, How to learn python and etc. Sentdex has a series of Youtube videos about Python for Finance. But you must have a basic understanding of python first before watching his videos.
Free Coursera Courses:
1. Python and Statistics for Financial Analysis (Week 6)
Coursera has some pretty good content as well, and some of them are free. But if you want to get the official certificate and put it on your Linkedin, then you have to pay a fee.
Books that I have Bought:
1. Python Crash Course (2nd Edition): A Hands-On, Project-Based Introduction to Programming
2. Automate The Boring Stuff With Python, 2nd Edition: Practical Programming for Total Beginners
Additionally, I have also googled and researched on the best book to learn python. All of them point towards the two books above. There are lots of universities and data scientists around the world that has used them as reference. I spent around $80 to buy both of them on Book Depository, the most expensive book that I have ever bought in my life. But it will definitely keep me occupied in 2020.
The reason why I also buy books is because you actually learn the foundation and concepts of python more proper when reading books. It gives you a stronger grasp of what is happening. I thought this was important because knowing python well could ease the transition towards more advanced topics like machine learning and AI in the future. That is the direction I intend to head towards.
Last but not least, I bought an additional Samsung monitor that is 24 inch for $148. A monitor screen would be your best friend when you start coding. I think this is the best investment I have ever made. It helps to improve productivity when learning python. One screen for video tutorials, one BIG screen for coding. Perfect learning environment!
The total amount I have invested in learning python to date is $300.
- $148 (Monitor screen)
- $80 (Books)
- $72 ($18 * 4 Udemy Courses)
Since there is nothing to invest in the stock market, dividend yields are all compressed, might as well invest in oneself. After all, the best investment is in yourself.