Undergraduate Course: Mathematical and computational methods in Geophysics (EASC09054)
Course Outline
School  School of Geosciences 
College  College of Science and Engineering 
Credit level (Normal year taken)  SCQF Level 9 (Year 3 Undergraduate) 
Availability  Available to all students 
SCQF Credits  20 
ECTS Credits  10 
Summary  This course introduces and develops mathematical and computational techniques commonly used in geophysics. The mathematics and computing are taught in an integrated manner so, for example, methods for finding an analytical solution to a differential equation are followed immediately by computing techniques for achieving the same aim. 
Course description 
In this course, you will learn a range of core mathematical and computational methods that form the basis for future courses.
1. Solve a variety of mathematical problems as applied in a geophysical context
2. Learn the basis about coding in Python
3. Break scientific problems down into computationally tractable programs
4. Write clear, working, well documented programs in Python
5. Solve ordinary and partial differential equations using numerical techniques
6. Understand the basis of Monte Carlo methods
The learning experience will be varied, mixing practical programming classes with traditional lectures and problemsolving tutorials. Where practical, we will reinforce the ideas from the mathematical methods within the computational classes.

Information for Visiting Students
Prerequisites  Mathematics including partial differentiation and differential equations. 
High Demand Course? 
Yes 
Course Delivery Information

Academic year 2018/19, Available to all students (SV1)

Quota: None 
Course Start 
Semester 1 
Timetable 
Timetable 
Learning and Teaching activities (Further Info) 
Total Hours:
200
(
Lecture Hours 18,
Seminar/Tutorial Hours 10,
Supervised Practical/Workshop/Studio Hours 30,
Feedback/Feedforward Hours 2,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
134 )

Assessment (Further Info) 
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %

Additional Information (Assessment) 
Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Coursework 50%, exam 50%. The exam will test the mathematical skills more than the computational ones, the coursework will do the reverse. Assessed Coursework will consist of one computing exercise (30% of course) and one set of mathematics problems (20% of course) One further set of maths problems and one further computing exercises will be marked for formative purposes. Completion of online Codecademy exercises is compulsory.
Formative Computation: Deadline Week 8
Assessed Computation: Deadline Week 11
Formative Mathematics: Deadline Week 6
Assessed Mathematics: Deadline Week 9
For more information regarding deadlines, please refer to the learn page.

Feedback 
Mathematical problems will be set every week, discussed in the tutorial and answers provided thereafter. The computation sessions will be run as interactive coding classes which encourage discussion and exploration of individual problems. In addition to the assessed coursework, one further set of maths problems and one further computing exercises will be marked for formative purposes. 
Exam Information 
Exam Diet 
Paper Name 
Hours & Minutes 

Main Exam Diet S1 (December)   2:30  
Learning Outcomes
On completion of this course, the student will be able to:
 Solve a variety of mathematical problems as applied in a geophysical context
 Write clear, working, well documented programs in Python
 Solve ordinary and partial differential equations using numerical techniques
 Understand the basis of Monte Carlo methods

Reading List
Sneider, R., Mathematical Methods for the Physical Sciences, 2004, Cambridge University Press, ISBN: 9780521834926.
Turcotte, D.,L. and Schubert, G. Geodynamics. Cambridge University Press. ISBN: 0521666244.

Additional Information
Graduate Attributes and Skills 
Programming in a highlevel computing language (Python) 
Keywords  Mathematics,geophysics,heat flow,programming,python 
Contacts
Course organiser  Dr Mark Naylor
Tel: (0131 6)50 4918
Email: Mark.Naylor@ed.ac.uk 
Course secretary  Ms Ashley Stein
Tel: (0131 6)50 8510
Email: v1astei5@exseed.ed.ac.uk 

