🐍 The Python Quants
Founder & CEO delivering Python, AI, quant finance, Crypto training and tooling for modern quants and engineers.
Visit TPQ ↗Educating the next generation of AI engineers with The AI Engineer program.
Founder of The Python Quants and The AI Machine. Author, educator, and builder empowering finance professionals and software engineers to accelerate quantitative finance with Python, AI, and automated research workflows.
I blend academic rigor with production-grade execution to empower finance professionals transitioning into an AI-first era.
With a Ph.D. in Mathematical Finance, I lead The Python Quants and The AI Machine, focusing on algorithmic trading, Python-driven analytics, and enterprise AI adoption. My work bridges research and industry impact through books, programs, and advisor roles.
Today, I partner with institutions and practitioners to build AI-native workflows: from LLM-assisted research pipelines to quantitative trading systems. My teams deliver portfolio-ready education, code assets, and community programs that help quants stay ahead.
Explore the ecosystem powering Python, quantitative finance, and generative AI adoption worldwide.
Founder & CEO delivering Python, AI, quant finance, Crypto training and tooling for modern quants and engineers.
Visit TPQ ↗Director of the renowned Certificate in Python for Finance — 400+ hours of video, tens of thousands of lines of code, and hundreds of interactive notebooks.
Learn about CPF ↗Flagship training program for AI-native builders. Ship production LLM systems with hands-on capstones.
Join TAE ↗Systematic training program for engineering crypto systems with confident. Primitives → Bitcoin → markets → live ops.
Join TCE ↗Advanced secure communication solutions (e.g. MagicCap for encrypted ephemeral chat).
Discover TAIM ↗Author of seven books on Python, quantitative finance, and applied AI for markets.
View catalog ↗Creating instructional video series and AI-powered informer videos and podcasts for the AI, Cryoti, and quant communities.
Watch on YouTube ↗Lecturer at CQF and EPAT programs, bringing advanced Python and AI workflows to practitioners.
CQF insights ↗Organizing meetups in London, New York, and beyond to grow the Python for finance network.
Join meetups ↗Leading developer community initiatives that align quant engineering with AI-native practices.
Explore community ↗Author of the DX Analytics Python package for valuation, risk analytics, and derivatives pricing.
Access GitHub ↗Rapidly developed with GenAI tooling, these papers and books capture key theses and frameworks driving myself, humanity in general, and our programs in particular.
Builds on the Newtonian volume to introduce Einstein's postulates, spacetime diagrams, Lorentz transformations, and four-vectors in a learner-friendly, fully worked mathematical narrative.
A from-first-principles tour of classical mechanics that builds the mathematical language alongside the physics. Combines visual intuition, worked examples, and just-enough formalism to make Newtonian ideas concrete for motivated learners across disciplines.
Recasts everyday habit building as a compact reinforcement learning problem. Using the MDP lens and the Bellman principle — choose what is good now and sets up good options next — Deep Q-Learning provides a simple loop: try, remember what worked, and refine with weekly reviews. Includes relatable examples and checklists for practical, improvable policies.
Extends the Deep Q-Life framework into a practical sobriety playbook. Maps alcohol cravings as Markov decision processes, designs replacement policies and experience replay rituals, and adds “soft” success factors such as mindfulness, future-self continuity, and self-compassion. Includes protocols and checklists for navigating high-risk situations and sustaining long-term alcohol-free living.
Argues that many founders, creatives, and executives display bimodal trait patterns — spending more time at both extremes and less in the middle — and translates this “paradoxical personality” profile into practical guidance for channeling those extremes without burning out.
Synthesizes the strongest human evidence for extending healthspan: a Mediterranean-style, protein- and fiber-rich diet, structured aerobic (including Zone 2) and resistance training, 7-9 hours of sleep, and intentional hydration. Completes the protocol with stress-regulation practices and social connection to counter the mortality impact of chronic isolation.
Explains why AI engineers act as modern digital alchemists — fusing data, models, systems, and governance to deliver reliable GenAI advantage — and why institutions must cultivate those capabilities through programs such as The AI Engineer.
Programming is still the engine of quantitative finance, and GenAI only amplifies — not replaces — the need for precise, testable code, disciplined workflows, and human-in-the-loop guardrails across research, models, and production systems.
An exploration of human-AI collaboration for quants. Learn how domain mastery and AI copilots combine to accelerate innovation.
A multiregional, comparative study of how AI and GenAI reshape higher education — documenting bottom-up student adoption, uneven institutional policy responses, and the widening AI/quant skills gap — while offering curricular strategies, assessment designs, and partnerships that keep finance programs aligned with modern demands.
A twin narrative — one story-driven, one mathematical — showing why, with minimal information, today's value is the statistically safest single-number forecast for both tomorrow's stock price and tomorrow's temperature, linking everyday intuition with conditional expectations and random-walk thinking.