From charlesreid1

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* Root Finding
* Root Finding


===Languages===
===Languages and Tools===


Languages:
* Java (solid)
* Python (solid)
* Go (minimal)
* C++ (minimal)
Tool categories:
* Built-in data structures (solid, comfortable with its API)
* Extended data structures (Pandas, Guava) and utilities (itertools, Apache Commons)
* Numerical libraries (big numbers, factoring, exponents, root finding, linear solvers, nonlinear solvers)
* Graph library
Infrastructure:
* Testing infrastructure & best practices (JUnit)
* Build tools (Bezel, Maven)


=Study Resources=
=Study Resources=

Revision as of 22:00, 11 July 2017

Computer Science: the science of computing. Or, the science of problem-solving with computers, computational devices, and computational methods.

Study Notes

See CS study plan repo for more detailed notes: https://charlesreid1.com:3000/cs/study-plan

Topics

Computer Science

Link: https://charlesreid1.com:3000/cs/study-plan/src/master/TODOSoftwareEngineering.md

CS list of topics:

Data Structures

Algorithms

Mathematics - Combinatorics and Probability

Mathematics - Number Theory

Mathematics - Numerics

Languages

Data Structures

For polished/digested study guides see: Study Guides

Link: https://charlesreid1.com:3000/cs/study-plan/src/master/TODOSoftwareEngineering.md

See also: Template:DataStructuresFlag

Algorithms

Algorithms

Algorithms can be divided into categories:

Programming practice and writeups:

Combinatorics and Probability

Number Theory

Numerics

Link: https://charlesreid1.com:3000/cs/study-plan/src/master/TODONumerics.md

Following the content of Numerical Recipes - algorithmic analysis, &c.

Numerics topics corresponding to particular chapters:

  • Linear algebra
  • Interpolation and Extrapolation
  • Root Finding

Languages and Tools

Languages:

  • Java (solid)
  • Python (solid)
  • Go (minimal)
  • C++ (minimal)

Tool categories:

  • Built-in data structures (solid, comfortable with its API)
  • Extended data structures (Pandas, Guava) and utilities (itertools, Apache Commons)
  • Numerical libraries (big numbers, factoring, exponents, root finding, linear solvers, nonlinear solvers)
  • Graph library

Infrastructure:

  • Testing infrastructure & best practices (JUnit)
  • Build tools (Bezel, Maven)

Study Resources

Some nice awesome lists:

Meta:

Programming tests:

Growth hacking:


Flags

Computer Science





See also:

Data Structures
































Algorithms







CS/OldPage