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GL5709: MACHINE LEARNING IN GEOPHYSICS (2021-2022)

Last modified: 31 May 2022 13:05


Course Overview

This module is designed to give students a range of skills associated with data-driven approaches and machine learning. Machine learning has revolutionised numerous scientific fields and it has begun to change the paradigm in geosciences by providing real-time solutions to non-trivial and computationally intense problems. Throughout the module the students will become familiar with the basic concepts and tools of machine learning. This will open up multiple career paths in geoscience and STEM in general.

Course Details

Study Type Postgraduate Level 5
Session Second Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Iraklis Giannakis
  • Dr Amy Gilligan

What courses & programmes must have been taken before this course?

  • Either Any Postgraduate Programme or MSc Geophysics

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

The course will provide the students with the essential skills for conceptually understanding and implementing machine learning approaches to geophysical and geological problems.

In particular, the course will start from the very basic concepts such as machine learning for regression and classification using simple neural networks and support vector machines. Subsequently, the student will become familiar with unsupervised learning and how to apply it for reducing the dimensions of the data. More advanced topics will be discussed such as optimisation methods in machine learning and techniques to mitigate overfitting. Lastly, recent advancements in machine learning and how to apply them in geophysical problems will be discussed i.e deep learning, convolutional neural networks, recurrent neural networks, long short-term memory and generative adversarial networks.

The lectures will be combined with practical sessions where the students will learn how to use Python tools to design machine learning solutions from scratch. Various datasets from different geological/geophysical problems will be provided in order for the students to practice in a diverse set of problems and learn how to apply machine learning accordingly. Within that context, introductory sessions will be given on Python with emphasis on data analysis and machine learning. 

 


Details for second half-session courses, including assessments, may be subject to change until 23 December 2022.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

  • 5 Lectures during University weeks 31 - 32
  • 2 Lectures during University week33

More Information about Week Numbers


Details for second half-session courses, including assessments, may be subject to change until 23 December 2022.

Summative Assessments

Practicals

Assessment Type Summative Weighting 50
Assessment Weeks Feedback Weeks

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Feedback

Feedback via MyAberdeen and email.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualApplyDiscover how Machine Learning is being applied to address geophysical problems
ConceptualUnderstandUnderstand the methods and terminology related to Machine Learning and Deep Learning
ProceduralAnalyseGain more experience in coding

Class Test

Assessment Type Summative Weighting 25
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

Feedback via MyAberdeen and email.

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualApplyDiscover how Machine Learning is being applied to address geophysical problems
ConceptualUnderstandUnderstand the methods and terminology related to Machine Learning and Deep Learning

Essay

Assessment Type Summative Weighting 25
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

Feedback via MyAberdeen and email.

Word Count 3000
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Formative Assessment

There are no assessments for this course.

Resit Assessments

None

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualUnderstandUnderstand the methods and terminology related to Machine Learning and Deep Learning
ConceptualApplyDiscover how Machine Learning is being applied to address geophysical problems
ProceduralAnalyseGain more experience in coding
ProceduralEvaluateGain more experience in writing scientific literature reviews

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