The aim of this course is to introduce the principles of engineering computations and probability and statistics. Its purpose is to provide foundation material for later year courses in water, structural and geotechnical engineering.
Availability2019 Course Timetables
- Semester 1 - 2019
On successful completion of the course students will be able to:
1. Apply basic numerical algorithms for computing solutions of single nonlinear equations and systems of linear equations.
2. Utilise algorithms for interpolation, curve fitting, numerical differentiation and numerical integration.
3. Apply numerical methods for solving ordinary differential equations, and elliptic and parabolic partial differential equations
4. Apply Bayesian inference in civil and environmental engineering applications.
5. Formulate and solve problems dealing with probability and statistics in civil and environmental engineering applications.
6. Develop practical skill in Monte Carlo simulation
The content of the course includes:
- The numerical solution of a single nonlinear equation, systems of linear equations, ordinary differential equations, and partial differential equations.
- The numerical implementation of interpolation and curve fitting.
- An introduction to probability and distribution theory targeted to civil and environmental engineering applications.
- Monte Carlo simulation: theory and practice.
- Introduction to Bayesian statistical inference with applications to the binomial and linear regression models.
To enrol in this course you must be active in one of the following Engineering programs: 12282, 12288, 12289, 12290, 12298, 12299 or 40005 or 10478.
Content covered in course ENGG1002 Introduction to Engineering Computations (previously GENG1002), and content covered in course MATH1120 Mathematics 2.
Written Assignment: Written Assignment 1
Written Assignment: Written Assignment 2
Written Assignment: Written Assignment 3
Written Assignment: Written Assignment 4
Quiz: Mid Term Quiz
Formal Examination: Formal Examination
Face to Face On Campus 4 hour(s) per Week for Full Term
Face to Face On Campus 2 hour(s) per Week for Full Term