Course Resources What you'll learn
Learn how to code in Python
Take your career to the next level
Work with Python’s conditional statements, functions, sequences, and loops
Work with scientific packages, like NumPy
Understand how to use the data analysis toolkit, Pandas
Plot graphs with Matplotlib
Use Python to solve real-world tasks
Get a job as a data scientist with Python
Acquire solid financial acumen
Carry out in-depth investment analysis
Build investment portfolios
Calculate risk and return of individual securities
Calculate risk and return of investment portfolios
Apply best practices when working with financial data
Use univariate and multivariate regression analysis
Understand the Capital Asset Pricing Model
Compare securities in terms of their Sharpe ratio
Perform Monte Carlo simulations
Learn how to price options by applying the Black Scholes formula
Be comfortable applying for a developer job in a financial institution
Requirements
You’ll need to install Anaconda. We will show you how to do it in one of the first lectures of the course
All software and data used in the course is free
Description
Do you want to learn how to use Python in a working environment?
Are you a young professional interested in a career in Data Science?
Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?
If so, then this is the right course for you!
We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.
An exciting journey from A-Z.
If you are a complete beginner and you know nothing about coding, don’t worry! We start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks.
Finance Fundamentals.
And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, we will focus on Finance, covering many tools and techniques used by finance professionals daily:
Rate of return of stocks
Risk of stocks
Rate of return of stock portfolios
Risk of stock portfolios
Correlation between stocks
Covariance
Diversifiable and non-diversifiable risk
Regression analysis
Alpha and Beta coefficients
Measuring a regression’s explanatory power with R^2
Markowitz Efficient frontier calculation
Capital asset pricing model
Sharpe ratio
Multivariate regression analysis
Monte Carlo simulations
Using Monte Carlo in a Corporate Finance context
Derivatives and type of derivatives
Applying the Black Scholes formula
Using Monte Carlo for options pricing
Using Monte Carlo for stock pricing
Everything is included! All these topics are first explained in theory and then applied in practice using Python.
Is there a better way to reinforce what you have learned in the first part of the course?
This course is great, even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context.
Who this course is for:
Aspiring data scientists
Programming beginners
People interested in finance and investments
Programmers who want to specialize in finance
Everyone who wants to learn how to code and apply their skills in practice
Finance graduates and professionals who need to better apply their knowledge in Python
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