Hi! I’m Martin – an MSc in Economic and Social Sciences from Bocconi University in Milan, Italy, and author of the Python, SQL, and Integration courses in the 365 Data Science Program. And I have fantastic news to share – we just launched our brand-new course – Python for Finance!
So, in this post, I’ll briefly explain what the Python for Finance course is all about. Then I’ll walk you through the structure of the course, the theory and practice it covers, and the in-demand skills it will help you master.
Finally, I’ll tell you a little bit more about myself and the co-author of the course – Ned.
The 365 Python for Finance Course
The goal of this course is to teach you how to combine programming in Python, financial data and analytical thinking to create independent analyses. In today’s data-driven business world, this highly prized skill will keep you ahead of the competition. Moreover, it will also help you stay on top of your personal investments.
This course assumes you feel at ease with just the fundamentals of coding in Python. However, if you’ve never coded or have never coded in Python, don’t worry. Because our Introduction to Python course will teach you the right amount of Python skills necessary for taking this course smoothly.
We did our best to create a course that will prepare you to handle real-life challenges with ease. That’s why we included both relevant topics in financial theory and their practical application in Python.
Who Is The Python For Finance Course For?
Python for Finance can be the perfect specialization for many.
So, maybe you’re a programmer who wants to learn more about finance and see how theory can be applied into practice using Python; a recent finance graduate or one with years of experience, striving to become independent in doing analyses in Python; an aspiring data scientist… Or you could simply be willing to organize your personal investments better. This course can add something truly significant to anyone’s skillset.
How Is The Course Structured?
Python for Finance includes 64 lectures, and more than 100 exercises and downloadable learning materials.
And I can say the course structure is quite efficient and easy-to-follow. First, Ned presents a topic in financial theory; then I use programming in Python to immediately apply it to real-world data. This way, by the time you finish the course, you’ll be confident doing diverse financial analyses.
What Will You Learn?
Here’s a summary of the sought-after skills the course will help you acquire:
- import the pandas-datareader module to download financial data
- calculate and compare Rates of Return in Python
- understand and measure Investment risk using Python
- use univariate and multivariate regressions for financial analysis
- Markowitz Portfolio Optimization in Python
- apply the Capital Asset Pricing Model (CAPM) formula, the Beta of a stock, the Sharpe ratio and other measures to real data with Python
- visualize the potential outcomes of financial operations and improve the associated risk estimation through Monte Carlo Simulations.
Exciting, right? So, if you’re curious to discover more details about each lecture, you can check out the extensive outline I’ve created on the Python for Finance Course Page.
About the Authors
As I mentioned, I am an Economic and Social Sciences graduate with advanced knowledge of Python programming, SQL, Mathematics, Statistics, Econometrics, Time-Series, and Behavioral Economics & Finance. In addition, my experience includes assisting in empirical research for Innocenzo Gasparini Institute of Economic Research. And working for DG Justice and Consumers at the European Commission where I dealt with data pre-processing; data quality checking; econometric and statistical analyses. You can learn more about me and my take on the most in-demand programming languages in my 365 Meet-the-Team Interview.
My friend and co-author of the course – Ned - has a bachelor’s degree in Business Administration and Management. He also has a Master’s degree in Finance at Bocconi University in Milan, Italy. Moreover, before he became co-founder of 365 Data Science, Ned had gained solid experience in financial advisory. Also, he has worked for several international companies, such as Pwc (Italy), Coca-Cola (United Kingdom), and Infineon Technologies (Germany). You can read Ned’s interview here.
The Python for Finance Course is part of the 365 Data Science Program. So, current subscribers can access the courses at no extra cost. To learn more about the 365 Data Science Program curriculum or enroll in the 365 Data Science Program, please visit our Courses page. Want to explore the curriculum or sign up 12 hours of beginner to advanced video content for free? Click on the button below.
