MATH 3511
Spring semester 2019

Julia Programming

Julia is a high-level, high-performance programming language for numerical computing

Why we created Julia

by Jeff Bezanson, Stefan Karpinski, Viral Shah, Alan Edelman

Julia cheatsheet

JuliaBox

"Run Julia in your browser. No setup."

JuliaPro Personal

"JuliaPro Personal is the fast, free way to install Julia on a Windows or Mac desktop or laptop and begin using it right now. It includes Julia compiler, profiler, Julia integrated development environment, 100+ curated packages, data visualisation and plotting."

Julia tutorials

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Julia official documentation

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Etiam porta sem malesuada magna mollis euismod rendered as bold text. Cras mattis consectetur purus sit amet fermentum le syndrome du clandestin. A clear, authoritative judicial holding on the meaning of a particular

\[ \begin{align} \nabla \times \vec{E} & = -\frac{\partial\vec{B}}{\partial t} \\ \nabla \cdot \vec{D} & = \rho_f \\ \nabla \times \vec{H} & = \vec{J}_f + \frac{\partial\vec{D}}{\partial t}\\ \nabla \cdot \vec{B} & = 0 \end{align} \]

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Resources

  1. Course textbook website
  2. Numerical computing
  3. Matlab
  4. Git and Gitlab
  5. Latex
  6. Julia

Course Archives

  1. Numerical Analysis I, Fall 2018
  2. Numerical Analysis II, Spring 2018

Links

  1. UConn AnyWare
  2. UConn SkyBox
  3. UConn GitLab
  4. UConn VPN
  5. UConn large file sharing
  6. UConn software

General

  1. Academic Calendar, Spring 2019
  2. UConn Math Department
  3. Dean of students
  4. 2019 Calendar of Religious Holidays
  5. Educational Rights and Privacy
  6. Office of the Provost's policies links