Pillars
- Quant finance path — MFE, Baruch, stochastic calc, risk, tradinginterview.com
- ML / data science path — CV, IML, PAI, deep learning, diffusion models
- Career & applications — Internships, ETH / Stanford / Baruch
Mid-goals
Quant finance path
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ODE, PDE w Financial Applications
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Analysis recap
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Probability and Statistics recap
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Probability Theory
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Introduction to Mathematical Finance
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Brownian Motion and Stochastic Calculus
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Mathematical Finance
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Topics in Mathematical Finance
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Applied risk management (UZH)
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tradinginterview.com
ML / data science path
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Computer Vision
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Recap IML
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Recap PAI
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Deep Learning
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Diffusion Model book
Baruch classes
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Advanced Calculus with Financial Engineering Applications (Oct 20 – Dec 15)
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Probability Theory for Financial Applications (Oct 21 – Dec 16)
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Numerical Linear Algebra for Financial Engineering (Oct 16 – Dec 18)
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Information Session (Dec 8)
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Machine Learning for Financial Engineering Applications (Feb 4 – Apr 1)