by The Python Quants
ALGORITHMIC TRADING & COMPUTATIONAL FINANCE
This unique program combines the Certificate Programs in Python for Algorithmic Trading (https://home.tpq.io/certificates/pyalgo) and Computational Finance (https://home.tpq.io/certificates/compfin) into one. With the Platinum Package, you get access to all our online training resources with about 200 hours live/recorded of instruction, 100s of pages PDF plus 1,000s of lines of Python code plus dozens of Jupyter Notebooks (read the 16 week study plan). Master AI-Driven Algorithmic Trading and Computation-First Finance with Python, get started today.
Enroll to the Platinum Package and benefit from the unique combination of materials, topics and codes that are covered in this comprehensive online training program. The regular fee is 3,095 EUR (net of VAT if applicable) per person. 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 firstname.lastname@example.org.
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.