Python Stock & Crypto Market Data Analysis Crash Course | Udemy


Python Stock & Crypto Market Data Analysis Crash Course | Udemy
English | Size: 231.66 MB
Genre: eLearning

40 min Crash course on fundamental concepts of Stock Market and Cryptocurrency Data Analysis with Python

What you’ll learn
Learn to compare Stock prices & Crypto prices
Learn about cumulating stock returns
Learn about visualizing Stock prices, returns, volatility & return distributions
Learn about correlation of Stocks and Cryptocurrencies

What is this course about?

In this 40 minute crash course I am going over fundamental concepts of Data Analysis of the Stock & Cryptocurrency Market using Python covering important topics:

– Pull prices for Stocks & Cryptocurrencies

– How to compare different stocks/cryptos using cumulative returns

– Volatility comparison

– Implications on volatility comparing stocks with cryptos

– How to visualize stock prices, volatilities and return distributions as well as Interpretation

– Correlation Analysis

Why should I be your constructor?

I got years of experience coding in Python and know which topics are key to understand to actually move on to topics like Data Analytics, Machine Learning, Data Science or Algorithmic Trading.

I wrote my Master Thesis on a quantitative Finance topic, currently working in the field of Data Science and got a YouTube channel teaching Algorithmic Trading and Data Science hands-on tutorials with over 60.000 subscribers.

Why this course?

This course is giving a rock solid foundation for anyone interested in learning Python in specific to apply it to above mentioned topics.

I am following a hands-on approach and you are getting the best out of this course if you code a long an analyze stocks, cryptos or other assets you are interested in.

There is not a single time filler and we are getting straight into the topics.

Any questions coming up?

If you got any questions please feel free to reach out! I am happy to hear from you.

Who this course is for:
Everyone interested in seeing what the surface of Python for Finance is looking like
Everyone who wants to work in field like data analysis, data science, quant finance, risk management

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