It’s helpful to use historical analogues combined with models built by others; but, this is a far cry from testing a hypothesis, verifying the robustness of models, and automating those ideas. Algorithms are replacing traders in banks and discretionary day traders. Those without modeling skills will find it tougher to compete going forward.
Thus, I’m going to be studying full time for a while, leaving open the possibility of returning to Graduate school for either a Masters in CS with a focus on Machine Learning or a MFE. It would probably be the former since the computer skills are more important than the high level math needed for pricing exotics, though the plan to mix in some of this as well.
A bubble in higher education exists, and while a technical degree is still worth its price, you can now get the equivalent of a Masters degree in Computer Science with Ivy League instruction, for free.
The skills weighted for this curriculum: Python, C++, Machine Learning, and Stats and Math, with less weight on other desired skills in Database Management, Parallel Computing, Linux, Web, and Natural Language Processing. This is only a preliminary curriculum and will change; preferably, by pruning the redundant C++ classes, while adding in more math.
- UC Berkley, Webcasts: tons of classes, but lacking assignments
- Stanford Curriculum; now offering certificates
- Harvard Curriculum; no assignments, on Itunes
- MIT; Assignments, some classes missing videos
- Google; limited, web focus.
- UC Berkley: Data Structures: Java
- UC Berkley: Operating Systems and System Programming:
- MIT: Structure and Interpretation of Computer Programs:
- Harvard: CSCI E-215 Unix/Linux Systems Programming:
- Harvard: CSCI E-292: Massively Parallel Computing:
- MIT: Introduction to CS and Programming: Python:
- MIT: Introduction to C++: C++:
- MIT: Introduction to C Memory Management and C++ Object-Oriented Programming
- Stanford :Python Programming Class, CodingBat:
- Stanford: Programming Abstractions I: C++
- Stanford: Programming Abstractions II: C++:
- Stanford: CS107 Programming Paradigms: C++: Pre 106B,
- Stanford: CS161 Design and Analysis of Algorithms, Archive: Pre Py,C++, Stats
- Stanford: CS345: Web Mining
- UC Berkley: Structure and Interpretation of Computer Programs: Python:
- UC Berkley: Computer Science 61A
- MIT: Economic History:
- Stanford: Game Theory:
- Stanford: Model Thinking:
- Stanford: Natural Language Programming: Java:
- Harvard: Building Dynamic Websites:
- Yale: Financial Markets:
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