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.