financial-data-science / CFDS

A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

Chartered Financial Data Scientist (CFDS) ®

A series of interactive lab notebooks we prepared for the DFVA and AZEK Chartered Financial Data Scientist (CFDS) ® Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

Cloning the repository to Azure Notebooks:

This is currently work in progress so please expect minor errors and some rough edges ;)

Seminar "Warm-Up" - Lab Notebooks

Lab 00: "Testing the CFDS Lab Environment" (, )

Lab 01: "Introduction to the CFDS Lab Environment" (, )

Lab 02: "Fundementals of Python Programming" (, )

First Seminar Day - Lab Notebooks

Lab 03: "Financial Data Science - Moving Average Trading Strategies" (, )

Lab 04: "Financial Data Science - Mean Reversion Trading Strategies" (, )

Lab 05: "Supervised Machine Learning - Naive Bayes, k-Nearest Neighbors" (, )

Lab 06: "Supervised Machine Learning - Support Vector Machines" (, )

Second Seminar Day - Lab Notebooks

Lab 07: "Unsupervised Machine Learning - k-Means Clustering, EM Algorithm" (, )

Lab 08: "Deep Learning - Artificial Neural Networks (ANNs)" (, )

Lab 09: "Deep Learning - Convolutional Neural Networks (CNNs)" (, )

Webinars - Lab Notebooks

Lab 10: "Deep Learning - Long Short-Term Memory Networks (LSTMs)" (, )

Lab 11: "Deep Learning - Autoencoder Neural Networks (AENNs)" (, )

(more lab notebooks to be published ...)

Getting Started

Install dependencies via pip install -r requirements.txt.

Questions?

Please feel free to get in touch by opening an issue report, submitting a pull request, or sending us an email.