FOR PYTHON QUANTS
An Exclusive Bootcamp Series Brought To You By CQF Institute And The Python Quants
LONDON TUE 12. TO THU 14. NOVEMBER 2019
THE SERIES IN NUMBERS
For those quants believing more in numbers than just words.
NYC + LONDON
PYTHON INFRASTRUCTURETue, 12. November 2019, One-day
Setting up Python environments for interactive financial analytics and application deployment.
A number of important tools and Python packages, illustrating the use of such packages as NumPy and pandas.
Introduces participants to a trading platform and its API as well as the Python wrapper packages.
Examples cover basic and first steps, working with historical financial data as well as streaming data and visualization.
TRADING STRATEGIESWed, 13. November 2019, One-day
Introduce participants to certain techniques to analyze historical financial data, in particular vectorized backtesting for algorithmic trading strategies based on typical financial indicators.
Different classification algorithms to derive algorithmic trading strategies will be discussed.
AUTOMATIONThu, 14. November 2019, One-day
You will be able to deploy and run algorithmic trading strategies in real-time, it is necessary to deal with streaming data and to transform offline algorithms to online algorithms
Important aspects when it comes to the robust and reliable deployment of algorithmic trading code.
Cloud deployment, logging and monitoring will be discussed.
BOOK A PACKAGE
Discount For Students applies to students.
Discount For Group Bookings when registering 3+ delegates
Discount When booking at least two bootcamps.
IMPRESSIONS FROM PREVIOUS EVENTS
MEET THE TEAM
Dr. Randeep Gug
Dr. Yves Hilpisch
Fitch Learning is a global leader in financial education with over 25 years of experience in delivering specialized, technical training to the finance community.
GET IN TOUCH TODAY!
DON'T MISS THIS UNIQUE OPPORTUNITY.
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The Experts in Data-Driven and AI-First Finance with Python. We focus on Python and Open Source Technologies for Financial Data Science, Artificial Intelligence, Algorithmic Trading and Computational Finance.