Abstract: 

This half-day trading session covers the most important Python topics and skills to apply AI and Machine Learning (ML) to Algorithmic Trading. The session shows how to make use of the Oanda trading API (via a demo account) to retrieve data, to stream data, to place orders, etc. Building on this, a ML-based trading strategy is formulated and backtested. Finally, the trading strategy is transformed into an online trading algorithm and is deployed for real-time trading on the Oanda trading platform.

Session Outline:
1. Module: Setting up the Python and Oanda (paper) trading infrastructure
2. Module: Financial data logistics and backtesting of a ML-based algorithmic trading strategy
3. Module: Deployment of the ML-based algorithmic trading strategy in real-time

Background Knowledge:
Basic knowledge of Python and data science packages, such as NumPy, pandas, and matplotlib.

Bio: 

Dr. Yves J. Hilpisch is founder and CEO of The Python Quants (http://tpq.io), a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, and computational finance. He is also founder and CEO of The AI Machine (http://aimachine.io), a company focused on AI-powered algorithmic trading based on a proprietary strategy execution platform.

Yves has a Diploma in Business Administration, a Ph.D. in Mathematical Finance and is Adjunct Professor for Computational Finance at Miami Herbert Business School.