Learn Python Programming and Conduct Real-World Financial Analysis in Python - Complete Python Training

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.

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 would need if you start working in a finance context.

Teaching is our passion.

Everything we will study has been explained in the best way possible. Plain and easy to understand English. Relevant examples. Time efficient videos. Don't forget to check out some of our sample videos and see they are easy to understand.

Course content
111 lectures 07:08:46

Welcome! Course Introduction
2 lectures 08:04

Introduction to programming with Python
7 lectures 33:22

Python Variables and Data Types
3 lectures 14:37

Basic Python Syntax
7 lectures 11:20

Python Operators Continued
2 lectures 07:45

Conditional Statements
4 lectures 13:29

Python Functions
7 lectures 18:31

Python Sequences
5 lectures 19:11

Using Iterations in Python
6 lectures 15:53

Advanced Python tools
16 lectures 01:04:10

PART II FINANCE: Calculating and Comparing Rates of Return in Python
10 lectures 42:55

PART II Finance: Measuring Investment Risk
10 lectures 41:24

PART II Finance – Using Regressions for Financial Analysis
4 lectures 21:39

PART II Finance – Markowitz Portfolio Optimization
4 lectures 19:34

Part II Finance – The Capital Asset Pricing Model
8 lectures 27:08

Part II Finance: Multivariate regression analysis
2 lectures 12:02

PART II Finance – Monte Carlo simulations as a decision-making tool
13 lectures 56:54

BONUS LECTURE
1 lecture 00:51

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