Do you want to learn how to use Python in a real 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 will start from the very basics. The first part of the course is ideal for beginners and people who want to brush up 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.
