Quant Bootcamp
6-day intensive training in Machine Learning for Quantitative Finance
Training in Machine Learning for Quantitative Finance
ARPM builds advanced statistical competence to work in modern financial engineering, risk management and quantitative investment
The next Certificate starts on September 23
Beyond-master online program: 5+5-month, multi-course, in-depth
Structured curriculum with live classes, support, and certification path
The next Quant Bootcamp starts on July 13 at New York University
Lab: Animations, Code, and Mathematics for Deeper Learning
What you will Learn
A complete, beyond master’s level curriculum that delivers unified understanding of Machine Learning and its applications to Financial Engineering, Risk Management and Quantitative Investment No gaps, no overlaps
Machine Learning
Quantitative Finance
Primers
How you will Learn
One advanced curriculum, three complementary ways to learn
Certificate in Machine Learning for Quantitative Finance
5+5-month, beyond-master program
Starts September 23
Lab
4,000-page e-textbook+AI tutor on Machine Learning for Quantitative Finance
Always available
Why ARPM?
Only ARPM has the Lab, a 4,000-page e-textbook on machine learning and its applications across all of quantitative finance, with code, animations, and an AI tutor, learn more.
E-Textbook
- No gaps, no overlaps. Most programs are taught on a collection of scattered references, with conflicting notation, overlapping topics and gaps. The Lab is written in succinct, unified, mathematical language and constantly updated for inclusiveness and consistency.
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Principles first.
Innovation in AI is chaotic and relentless: to remain competitive you need to understand the core
principles behind any new techniques. The Lab is structured around
- The “Machine Learning Ecosystem" – a framework for organizing all of Machine Learning from the simplest principles to the most advanced innovations, learn more.
- The “10-Step Checklist of Finance” – a framework for organizing the entire fields of Financial Engineering, Risk Management and Quantitative Investment, learn more.
Our Stats
5,000+ alumni
Quant Bootcamp-ers and Certificate holders, since 2009
100,000+ Lab code lines
All case studies and examples implemented on Jupyter Lab, no installation required
3,500+ Lab pages
Overarching notation across Machine Learning and Quantitative Finance
Testimonials
- Leif Andersen - Global Co-Head of Quantitative Analytics, Bank of America
- Boris Deychman - Head of Model Risk Management, DTCC
- Mike Sternberg - Global Head Of Aladdin Financial Engineering, BlackRock
These professionals chose ARPM for team upskilling. While company policy restricts official endorsements, they are happy to provide personal references upon request. All views expressed are their own and do not necessarily reflect those of their employers.