COMP2710 Special Topics in Computer Science

Welcome to Numerical Computing with Julia, Semester 2 2023!

Special Case Course Enrollment

You may need a permission code to enrol (I knew some Master students needed it). If so, please submit a request here. This process is managed by Student Services.

Course Information (Outline available here)

• Mode of Delivery: In Person
• Class Meeting Time: Fridays 12:00 pm - 14:00 pm
• Class Meeting Location: Room 5.06, Marie Reay Building #155
• Lab Meeting Time: Mondays 14:00 pm - 16:00 pm
• Lab Meeting Location: CSIT N109
• Course Prerequisites:
  • COMP1100/1110/1130/1140/1730; In other words, some basic knowledge of programming.
  • Existing knowledge of Julia, calculus, and linear algebra will make the course easier.

Course Staff

Course Convener and Lecturer

• Name: Quanling Deng
• Email: COMP2710.convenor@anu.edu.au (please address all the course-related questions to this functional mailbox)
• Office Location: 4.19 @ Building #145, Hanna Neumann or virtually at Zoom
• Consultation Hour: Fridays 14:00 pm - 15:00 pm or by appointment

Tutors

• Name: Jipei Chen
• Email: Jipei.Chen@anu.edu.au

Course Description

This is an introductory course on numerical computation with a focus on computer program realization using Julia. The course covers topics such as roots of non-linear equations, function approximation with series expansions, polynomial interpolation and data fitting, algorithms for solving linear systems of equations, quadrature rules for numerical integration, difference rules for numerical differentiation, and a tentative topic on numerical methods for differential equations. Emphasis is made on algorithm development implementation in Julia and the basic mathematical ideas behind the algorithms. Learning to use Julia will be an important part of the course.

Course Learning Outcomes

• Demonstrate basic knowledge of programming in Julia.
• Demonstrate basic knowledge of numerical differentiation/integration, interpolation, and data fitting.
• Be able to implement numerical computation algorithms such as root-finding, expansion, interpolation/data fitting, matrix calculation, and numerical integrations.

References

• Bezanson, Jeff, Alan Edelman, Stefan Karpinski, and Viral B. Shah. “Julia: A fresh approach to numerical computing.” SIAM Review 59, no. 1 (2017): 65-98.

• Tobin A. Driscoll, Richard J. Braun. Fundamentals of Numerical Computation: Julia Edition (freely available here)

Additional resources

• The official list of Julia’s learning resources https://julialang.org/learning/
• Julia’s Youtube channel https://www.youtube.com/user/JuliaLanguage
• A package on Fundamentals of Numerical Computation
• A guide: https://github.com/gridap/Gridap.jl/wiki/Start-learning-Julia