in Python for Algorithmic Trading
by The Python Quants
Master AI-Driven Algorithmic Trading
Comprehensive Online Training Program
This is an intense online training program about Python techniques for algorithmic trading. By signing up to this program you get access to 150+ hours of live/recorded instruction, 1,200+ pages PDF as well as 5,000+ lines of Python code and 50+ Jupyter Notebooks (read the 16 week study plan). Master AI-Driven Algorithmic Trading, get started today.
Build your own algorithmic trading business.
The next Certificate Program starts 2020, is mostly self-paced and takes about 16 weeks to complete. Read the example 16 week study plan. Classes include Finance with Python, Python Tools & Skills, Python for Financial Data Science, Python for Algorithmic Trading, Artificial Intelligence in Finance, Python for Excel, Python for Databases and Natural Language Processing.
Get in touch if you think you qualify for a discount (e.g. students, academics, upgrades from other TPQ classes/courses).
With the Platinum Package you get access to all our online training resources. Enrolling to this package signals that you are serious about improving your Python skills.
If you are signing up as an individual or in the name of a German corporation, use this button:
If you are booking in the name of a EU-based (excl. Germany) or international cooperation, do it here:
Cancellations or refunds are not possible since delegates get full access to the complete electronic program materials (videos, HTML pages, PDFs, Jupyter Notebooks, Python codes, etc.). The program resources are copyrighted and not allowed to be shared or distributed. The resources are instructional and illustrative only. They come with no warranties or representations, to the extent permitted by applicable law.
Login credentials to the Quant Platform are sent immediately afterwards, so you can get started with the course materials right away. Detailed joining instructions for the live sessions will be sent in time before they start.
Frequently Asked Questions
The program covers a wide range of important topics in Python for Finance & Algorithmic Trading, such as vectorized & event-based backtesting, streaming data & socket programming, machine & deep learning as well as live trading on popular trading platforms. Among others, you get access to 150+ hours of recorded/live instruction, 1,200+ pages documentation, 5,000+ lines of Python code, 50+ Jupyter Notebooks. There are also tutorials with exercises and test projects. Towards the end, you take part in practice modules and prepare a final, graded project.
We expect you to have some programming experience (not necessarily Python) and some background in finance. Our Finance with Python course provides a gentle introduction to finance from fundamental principles and to Python from scratch.
We know that many of you have full-time jobs and other commitments. Therefore, we are fully flexible with regard to timings. If you prefer, you can do the program completely self-paced.
We do not limit access to the resources of the program. To the contrary, you benefit from certain updates that we will bring out in the future automatically.
Yes, there are live sessions in addition to the large number of recorded sessions available. We are used to having delegates basically from around the world. Therefore, all sessions are recorded and made available shortly afterwards since not everybody can follow every live session — be it due to time zone differences or due to other commitments.
Immediately after signing up, you get access to all the materials and video recordings. This allows you to orient yourself on the Quant Platform and to review the introductory lessons.
We offer a 15% discount for students and academics. We also offer special upgrade prices for those who have already booked a course or class with us. Just reach out to us via email@example.com.
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.