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DRPS : Course Catalogue : School of Geosciences : Earth Science

Undergraduate Course: Geophysical Data Science (EASC08025)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 8 (Year 2 Undergraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryIn Geophysical Data Science you will learn the basics of scientific computing using Python. The course balances the development of fundamental computing skills and the application of these for data presentation and analysis. You will work with a range of solid earth and climate + met datasets in order to practice these data analysis skills. These skills will prepare you for data analysis in project work, set you up to understand computational modelling and give you transferable coding skills in a computing language that is highly sought after in industry.
Course description Week 1: Introduction to Python for Data Science and Scientific Computing
Week 2: Intermediate Python for Data Science
Week 3: Data Visualisation with Python
Week 4: Data Ingestion and Cleaning
Week 5: Geospatial Data Analysis
Week 6: Statistical and Trend Analysis
Week 7: Understanding Data using Probability
Week 8: Geophsical Time Series Data
Week 9: Meteorological and Climate Data
Week 10: Assessment - Climate Data Analysis
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  27
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 98 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
¿ Feedback from lecturers and demonstrators during the interactive computing sessions
¿ Ongoing feedback from the online python learning environment
¿ Class discussion on the geophysics graph gallery contributions
¿ Written feedback on the assessed coursework
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand the role of coding in geophysical data analysis and modelling
  2. Build a foundation for scientific computing using Python
  3. Build confidence in using Python to model geophysical data
  4. Be able to undertake exploratory data analysis using a range of geophysical data, including choosing how to present data and extract statistical properties
  5. Learn how to use the internet to find appropriate pieces of code to hack to solve a new problem
Reading List
Edina's Noetable server:
Additional Information
Graduate Attributes and Skills - Data literacy: Scientific computing and data analysis
- Computer literacy: competency in Python
- Working in small groups
Additional Class Delivery Information One weekly 3 hour combined lecture and practical class.
KeywordsGeophysics,data science,python,coding
Course organiserDr Mark Chapman
Tel: (0131 6)50 8521
Course secretaryMr Johan De Klerk
Tel: (0131 6)50 7010
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