Study Tracking

I really like making plans for things to study. Sometimes I even finish!

To clarify the difference between this and the reading list:

• reading is me going through a book and (hopefully) remembering some content.
• studying is me actively putting effort into long term recall. This usually means homework exercises and exams, but can also be oral exams and presentations, spaced repetition, etc.

Planned

CS

• C compiler
  • Dragon book
  • Engineering a Compiler book
• Computer Networks
  • Brown CS 168
• Monte Carlo simulations
• Physics simulations

Math

• “Honors” mathematical statistics
  • MIT 18.650
  • CMU 36-705
  • Stanford Stats 200
• Applied statistics
  • CMU 36-707
  • Stanford Stats 203
• Stochastic processes / “honors” discrete math
  • Mitzenmacher & Upfal
• Statistical / “honors” ML
• Information theory
• Differential equations
• Fourier analysis

Finance

• Investing
  • Bodie, Kane, and Marcus
• Some kind of practical quant finance / advanced investing
  • Programming projects (do it myself!)
  • Lopez de Prado
  • Trading systems books

Completed

2021

• MIT 6.046 Analysis of Algorithms

Major study books:

• CLRS, Introduction to Algorithms
  • All starred and end of chapter problems completed

Supplemental books:

2020

• MIT 6.006 Introduction to Algorithms
• MIT 6.001 Structure and Interpretation of Computer Programs

• MIT 15.501 Introduction to Financial and Managerial Accounting

• C++ programming:
  • MIX simulator and assembler project

Major study books:

• Abelson & Sussman, SICP
  • All written exercises complete
  • Coding exercises through partway Ch 3 complete
• CLRS, Introduction to Algorithms
  • All starred and end of chapter problems completed through Ch 17

Supplemental books:

• Skiena, The Algorithm Design Manual
• Knuth, The Art of Computer Programming: Volume 1
• Pratt, Financial Accounting in an Economic Context

2019

• Microeconomics (combined):
  • MIT 14.01 Principles of Microeconomics
  • MIT 14.04 Intermediate Microeconomic Theory

• MIT 18.600 Probability and Random Variables

• C++ programming practice
  • some Leetcode questions
  • some C++ books including:
    • Effective C++
    • Effective STL
    • Effective Modern C++
    • A Tour of C++
• Work lecture series
  • Basic machine learning
  • Some topics in deep learning
  • Basic theoretical statistics

Supplemental books:

• Varian, Intermediate Microeconomics
• Ross, A First Course in Probability
• Murphy, Machine Learning: a Probabilistic Perspective
• Goodfellow et al, Deep Learning
• Rice, Mathematical Statistics and Data Analysis

2018

I bought a bunch of books but didn’t get through most of them. Nothing organized completed this year.

Supplemental books:

• Russell & Norvig, Artificial Intelligence: A Modern Approach
• Murphy, Machine Learning: a Probabilistic Perspective
• Hastie et al, The Elements of Statistical Learning
• Hastie et al, Introduction to Statistical Learning
• Rice, Mathematical Statistics and Data Analysis

And a brief, aborted stab at Knuth’s Art of Computer Programming (hah!).

This is around when I realized it’s much harder to study while working full-time and not actively required to. This list is one way to start fixing things…

2017

Mid-2017 is when I finished my PhD in pure math. Before then all my studying energy went into getting that done. But afterwards I did get through some things while preparing to find a job.

• Probability (MIT 6.041 Applied Probability)
• Statistics (DeGroot & Schervish, Ch 6-8)
• ML (Hastie et al, Ch 1-3)
• CS and Finance interview prep (Gayle, Crack)

Abandoned

2020

MIT 15.433 Investments

• This course is too easy for the material. Lots of multiple choice and simplistic questions. Not enough hard stuff. Not enough programming.

2019

MIT 14.02 Principles of Macroeconomics

• This material is not valuable for my needs. Wrong path for success.

Skeina, Algorithm Design Manual

• Ch 1 complete (2019-08-03)
• The exercises in this book are not exciting enough.
• Better for me: Cormen, MIT, Knuth, Leetcode

Goals (2019)

This is to track ongoing personal goals. At some point I should add some historical goals here too.

Practices (see Results vs Practices

• No internet – 4 weeks (since 2019-07-20). (Previous record: about 70 days).
• Writing 3x / week, at least 5 minutes each time – just started (since 2019-08-17).
• Home study 2x / week, at least 1 hour each time – 4 weeks (since 2019-07-20).
• Math/CS eclectic reading 3x/week, at least 15 minutes each time – 2 weeks (since 2019-08-03).