Learn Python Programming and Conduct Real-World Financial Analysis in Python – Complete Python Training
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
- 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
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 Beginner to Pro.
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.
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
- 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
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