Python Finance Data Analysis – A Productive Kickstart

Python Finance Data Analysis by Al Ardosa

Python Finance Data Analysis Excited Roadmap!

Python Finance Data Analysis – Risk-free Ready!

Learn:
-Codes in Python
-Career to the next level
-Conditional statements, functions, sequences, and loops
-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

Python Finance Data Analysis Guide!

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.

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?

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.

Teaching is our passion.

Everything we teach is explained in the best way possible. Plain and clear English, relevant examples and time-efficient videos. Don’t forget to check some of our sample videos to see how easy they are to understand.

If you have questions, contact us! We enjoy communicating with our students and take pride in responding within the 1 business day. Our goal is to create high-end materials that are fun, exciting, career-enhancing, and rewarding.

What makes this course different from the rest of the Programming and Finance courses out there?

Teach you how to code in Python and apply these skills in the world of Finance. It is both a Programming and a Finance course.

Just subscribe to this course! If you don’t acquire these skills now, you will miss an opportunity to separate yourself from the others. Don’t risk your future success! Let’s start learning together now!
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

Python Finance Data Analysis by Al Ardosa
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