Python for Finance: Investment Fundamentals & Data Analytics
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Python for Finance: Investment Fundamentals & Data Analytics

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

Created by 365 Careers
9 hours
Video Content
141
Lectures
138,769
Students
4.4
Rating
4.4
(138,769 students enrolled)

What you'll learn

βœ“Learn how to code in Python
βœ“Take your career to the next level
βœ“Work with Python’s conditional statements, functions, sequences, and loops
βœ“Work with scientific packages, like NumPy
βœ“Understand how to use the data analysis toolkit, Pandas
βœ“Plot graphs with Matplotlib
βœ“Use Python to solve real-world tasks
βœ“Get a job as a data scientist with Python
βœ“Acquire solid financial acumen
βœ“Carry out in-depth investment analysis
βœ“Build investment portfolios
βœ“Calculate risk and return of individual securities
βœ“Calculate risk and return of investment portfolios
βœ“Apply best practices when working with financial data
βœ“Use univariate and multivariate regression analysis
βœ“Understand the Capital Asset Pricing Model
βœ“Compare securities in terms of their Sharpe ratio
βœ“Perform Monte Carlo simulations
βœ“Learn how to price options by applying the Black Scholes formula
βœ“Be comfortable applying for a developer job in a financial institution

Course Content

20 sections β€’ 141 lectures β€’ 09:13:34 total length

Welcome! Course Introduction

2 lectures β€’ 08:04

What Does the Course Cover?05:10
Download Useful Resources - Exercises and Solutions02:54

Introduction to programming with Python

7 lectures β€’ 29:43

Programming Explained in 5 Minutes05:03
Programming Explained in 5 Minutes2 questions
Why Python?05:11
Why Python?2 questions
Why Jupyter?03:29
+6 more lectures

Python Variables and Data Types

6 lectures β€’ 26:06

Variables04:51
Python Coding Exercises - Part I04:58
Variables - Exercise #11 question
Variables - Exercise #21 question
Variables - Exercise #31 question
+18 more lectures

Basic Python Syntax

7 lectures β€’ 11:29

Arithmetic Operators03:23
Arithmetic Operators - Exercise #11 question
Arithmetic Operators - Exercise #21 question
Arithmetic Operators - Exercise #31 question
Arithmetic Operators - Exercise #41 question
+25 more lectures

Python Operators Continued

2 lectures β€’ 07:45

Comparison Operators02:10
Comparison Operators - Exercise #11 question
Comparison Operators - Exercise #21 question
Comparison Operators - Exercise #31 question
Comparison Operators - Exercise #41 question
+9 more lectures

Conditional Statements

4 lectures β€’ 13:33

Introduction to the IF statement03:01
IF - Exercise #11 question
IF - Exercise #21 question
Introduction to the IF statement1 question
Add an ELSE statement02:45
+6 more lectures

Python Functions

7 lectures β€’ 18:35

Defining a Function in Python02:02
Creating a Function with a Parameter03:49
Creating a Function - Exercise #11 question
Creating a Function - Exercise #21 question
Another Way to Define a Function02:36
+18 more lectures

Python Sequences

5 lectures β€’ 19:06

Lists04:02
Lists - Exercise #11 question
Lists - Exercise #21 question
Lists - Exercise #31 question
Lists - Exercise #41 question
+29 more lectures

Using Iterations in Python

8 lectures β€’ 26:14

For Loops02:56
For Loops - Exercise #11 question
For Loops - Exercise #21 question
For Loops1 question
While Loops and Incrementing02:26
+17 more lectures

Advanced Python tools

16 lectures β€’ 01:04:10

Object Oriented Programming05:00
Object Oriented Programming - Quiz2 questions
Modules and Packages01:05
Modules - Quiz2 questions
The Standard Library02:47
+16 more lectures

PART II FINANCE: Calculating and Comparing Rates of Return in Python

10 lectures β€’ 42:48

Considering both risk and return02:33
Risk and return - Quiz1 question
What are we going to see next?02:34
Calculating a security's rate of return05:31
Calculating a security's rate of return1 question
+9 more lectures

PART II Finance: Measuring Investment Risk

10 lectures β€’ 41:24

How do we measure a security's risk?06:05
Which of the following sentences is true? - Quiz1 question
Calculating a Security’s Risk in Python05:55
The benefits of portfolio diversification03:28
Investing in stocks - Quiz1 question
+10 more lectures

PART II Finance - Using Regressions for Financial Analysis

4 lectures β€’ 21:39

The fundamentals of simple regression analysis03:55
Regressions - Quiz1 question
Running a Regression in Python06:35
Are all regressions created equal? Learning how to distinguish good regressions04:55
Regressions - Quiz1 question
+1 more lectures

PART II Finance - Markowitz Portfolio Optimization

4 lectures β€’ 19:34

Markowitz Portfolio Theory - One of the main pillars of modern Finance06:34
Markowitz - Quiz1 question
Obtaining the Efficient Frontier in Python – Part I05:35
Obtaining the Efficient Frontier in Python – Part II05:18
Obtaining the Efficient Frontier in Python – Part III02:07

Part II Finance - The Capital Asset Pricing Model

8 lectures β€’ 27:08

The intuition behind the Capital Asset Pricing Model (CAPM)04:44
CAPM - Quiz1 question
Understanding and calculating a security's Beta04:14
Beta - Quiz1 question
Calculating the Beta of a Stock03:38
+8 more lectures

Part II Finance: Multivariate regression analysis

2 lectures β€’ 12:02

Multivariate regression analysis - a valuable tool for finance practitioners05:42
Multivariate Regressions - Quiz1 question
Running a multivariate regression in Python06:20

PART II Finance - Monte Carlo simulations as a decision-making tool

13 lectures β€’ 56:54

The essence of Monte Carlo simulations02:31
Monte Carlo - Quiz1 question
Monte Carlo applied in a Corporate Finance context02:30
Monte Carlo in Corporate Finance - Quiz1 question
Monte Carlo: Predicting Gross Profit – Part I06:03
+13 more lectures

APPENDIX - pandas Fundamentals

15 lectures β€’ 01:10:03

pandas Series - Introduction08:33
A Note on Completing the Upcoming Coding Exercises01:22
Python Coding Exercises - Part II05:35
pandas Series - Exercise #11 question
pandas Series - Exercise #21 question
+65 more lectures

APPENDIX - Technical Analysis

10 lectures β€’ 36:12

Technical Analysis - Principles, Applications, Assumptions02:56
Charts Used in Technical Analysis05:32
Other Tools Used in Technical Analysis01:52
Trend, Support and Resistance Lines03:56
Common Chart Patterns04:25
+5 more lectures

BONUS LECTURE

1 lectures β€’ 01:02

Bonus Lecture: Next Steps01:02

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? Β 

Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems? Β 

If so, then this is the right course for you! Β 

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. Β 

An exciting journey from Beginner to Pro.Β  Β 

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.Β  Β 

Finance Fundamentals. Β 

And it gets even better! The Finance part 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:Β  Β 

  • Rate of return of stocks Β 

  • Risk of stocks Β 

  • Rate of return of stock portfolios Β 

  • Risk of stock portfolios Β 

  • Correlation between stocks Β 

  • Covariance Β 

  • Diversifiable and non-diversifiable risk Β 

  • Regression analysis Β 

  • Alpha and Beta coefficients Β 

  • Measuring a regression’s explanatory power with R^2 Β 

  • Markowitz Efficient frontier calculation Β 

  • Capital asset pricing model Β 

  • Sharpe ratio Β 

  • Multivariate regression analysis Β 

  • Monte Carlo simulations Β 

  • Using Monte Carlo in a Corporate Finance context Β 

  • Derivatives and type of derivatives Β 

  • Applying the Black Scholes formula Β 

  • Using Monte Carlo for options pricing Β 

  • Using Monte Carlo for stock pricing

Everything is included! All these topics are first explained in theory and then applied in practice using Python. This is the best way to reinforce what you have learned.Β  Β 

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.Β Β  Β Β 

Teaching is our passion. Β 

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

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

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

  • This course will 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.

  • High-quality production – HD video and animations (this isn’t a collection of boring lectures!)

  • Knowledgeable instructors. Martin is a quant geek fascinated by the world of Data Science, and Ned is a finance practitioner with several years of experience who loves explaining Finance topics in real life and on Udemy.

  • Complete training – we will cover all the major topics you need to understand to start coding in Python and solving the financial topics introduced in this course (and they are many!)

  • Extensive case studies that will help you reinforce everything you’ve learned.

  • Course Challenge: Solve our exercises and make this course an interactive experience.

  • Excellent support: If you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day.

  • Dynamic: We don’t want to waste your time! The instructors set a very good pace throughout the whole course.

Please don’t forget that the course comes with Udemy’s 30-day unconditional, money-back-in-full guarantee. And why not give such a guarantee, when we are convinced the course will provide a ton of value for you?

Click 'Buy now' to start your learning journey today. We will be happy to see you inside the course.

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

This course includes:

  • 9 hours on-demand video
  • 2 articles
  • 88 downloadable resources
  • Access on mobile and TV
  • ∞Full lifetime access
  • Certificate of completion

Instructor

365 Careers

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