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Tools for Data Science > IBM
Presented by Aije Egwaikhide, Romeo Kienzler, and Svetlana Levitan
In this course, you'll learn about Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio.
Executive Programme in Algorithmic Trading (EPAT®)
Presented by
Learn Algorithmic Trading - Build your Career in Algorithmic Trading
QuantLib Python Cookbook

QuantLib Python Cookbook:
Quantitative finance in Python.

Goutham Balaraman and - Luigi Ballabio
A hands-on, interactive look at the QuantLib library through the use of Jupyter notebooks as working examples.

Foundations of Computational Finance with MATLAB®

Foundations of Computational Finance with MATLAB®:
Graduate from Excel to MATLAB® to keep up with the evolution of finance data.

Ed McCarthy -
Foundations of Computational Finance with MATLAB® is an introductory text for both finance professionals looking to branch out from the spreadsheet, and for programmers who wish to learn more about finance.

An Introduction for Statistical Learning (with R examples)

An Introduction for Statistical Learning (with R examples):
Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani -
This book presents some of the most important modeling and prediction techniques in Statistical Learning as well as exploring relevant applications.

Quantitative finance with R and cryptocurrencies

Quantitative finance with R and cryptocurrencies:
Dean Fantazzini -
The aim of this book is to provide the necessary background to analyse cryptocurrencies markets and prices using quantitative techniques.


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