Web scraping and data analysis with Python

Web scraping and data analysis with Python, available at $54.99, with 20 lectures.

You will learn about Get an insight on data acquisition and data analysis processes using financial data from yahoo finance as a test-bed Get an introduction into HTML and its main tags/elements for understanding a webpage structure Obtain a first understanding of BeautifulSoup as a means for scraping data from a webpage Preprocess data in Python using Pandas Manage and extract further information out of the scraped ESG rating score data Get an introduction into Markowitz portfolio theory for data analysis based on a (constrained) optimization approach Incorporate the ESG rating score data into Markowitz' portfolio theory and assess the effect on the risk and return This course is ideal for individuals who are This course is for anyone who is interested in applying python for web scraping and data analysis associated with financial, i.e, stock market and ESG rating score data It is particularly useful for This course is for anyone who is interested in applying python for web scraping and data analysis associated with financial, i.e, stock market and ESG rating score data.

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Summary

Title: Web scraping and data analysis with Python

Price: $54.99

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Get an insight on data acquisition and data analysis processes using financial data from yahoo finance as a test-bed
Get an introduction into HTML and its main tags/elements for understanding a webpage structure
Obtain a first understanding of BeautifulSoup as a means for scraping data from a webpage
Preprocess data in Python using Pandas
Manage and extract further information out of the scraped ESG rating score data
Get an introduction into Markowitz portfolio theory for data analysis based on a (constrained) optimization approach
Incorporate the ESG rating score data into Markowitz' portfolio theory and assess the effect on the risk and return

Who Should Attend

This course is for anyone who is interested in applying python for web scraping and data analysis associated with financial, i.e, stock market and ESG rating score data

Target Audiences

This course is for anyone who is interested in applying python for web scraping and data analysis associated with financial, i.e, stock market and ESG rating score data

Have you ever wondered how web scraping works and what added value you can gain from the extracted data? Plus the opportunity to get more information by analyzing data in an end-to-end project in Python? Then this is the right course for you!

In this course “Web Scraping and Data Analysis with Python – A Practical Introduction Applied to ESG Rating and Stock Market Data,” I will provide you a comprehensive introduction on how to apply web scraping and data analysis approaches in Python using financial data from Yahoo Finance as a test-bed. After a brief insight into HTML, we will cover the essentials of web scraping using BeautifulSoup, a well-known library in Python, in order to extract a series of ESG (Environmental, Social, and Governance) scores along with their underlying stock prices.

In turn, we will move to the data analysis part, where we will conduct portfolio optimizations based on the Markowitz model. There, you will get familiar with the approaches on how to perform a classic portfolio optimization and then enhance it by incorporating the ESG scores obtained from the web scraping part. This will help you gaining an understanding on how to make data-driven decisions in finance, and to assess the effect between the risk/return profile and sustainability factors.

By the end of this course, you will obtain the skills to build your own web scraping and data analysis projects in Python, enabling you to extract valuable information from the web and turn it into actionable insights.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course introduction

Lecture 2: Installation / setup of the development environment

Chapter 2: Web Scraping with Python

Lecture 1: General considerations

Lecture 2: Introduction to HTML – I

Lecture 3: Introduction to HTML – II

Lecture 4: Introduction to HTML – III

Lecture 5: Introduction to BeautifulSoup

Lecture 6: Scraping the 'test.html' file

Lecture 7: Scraping a webpage

Chapter 3: ESG Data

Lecture 1: General considerations

Lecture 2: Scraping an ESG score from one stock of the Swiss Market Index (SMI)

Lecture 3: Scraping all ESG scores of the SMI stocks

Lecture 4: ESG score distribution across company sectors

Chapter 4: Data analysis using the ESG scores

Lecture 1: Portfolio selection – The Markowitz model

Lecture 2: Example – Minimum variance portfolio of two stocks

Lecture 3: Implementation: Minimum variance portfolio of SMI

Lecture 4: Markowitz goes green – The portfolio selection model extended with ESG

Lecture 5: Implementation: Minimum variance portfolio of SMI with ESG

Lecture 6: Efficient frontier calculation as function of ESG score

Chapter 5: Summary and outlook

Lecture 1: Summary and outlook

Instructors

Dimitrios Koulialias PhD
Physicist | Data & Python enthusiast | Udemy instructor

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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