PX5930: Planetary and Data Science Project

PX5930: PLANETARY AND DATA SCIENCE PROJECT (2026-2027)

Last modified: 10 Sep 2026 09:46

Course Overview

This is the dissertation course for the MSc Planetary and Data Science. It is intended to allow students to undertake a piece of in-depth work in a topical area relevant to their interests and degree topic to showcase their skills in the application of data science to planetary systems.

Course Details

Study Type	Postgraduate	Level	5
Term	Third Term	Credit Points	60 credits (30 ECTS credits)
Campus	Aberdeen	Sustained Study	No
Co-ordinators	Dr M. Carmen Romano Dr Anshuman Bhardwaj

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

Any Postgraduate Programme (Studied)

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?

Course Description

This course is intended to allow students to undertake a significant piece of work examining the use of data sciences approaches in the analysis of planetary systems. The project involves independent study into a topic supervised by a member of staff, although students also have the opportunity to suggest their own projects areas, and projects could be carried out in collaboration with industry partners.

The completion of the dissertation project typically calls on the integration of the various taught elements students have been exposed to and is assessed on the basis of a substantive dissertation alongside an oral examination of the work carried out.

Details, including assessments, may be subject to change until 21st September 2026 for Term 1 and Full Year courses and 8th January 2027 for Term 2 courses.

Summative Assessments

Project Report/Dissertation

Assessment Type	Summative	Weighting	70
Assessment Weeks	5	Feedback Weeks	8	Look up Week Numbers
Feedback	Dissertation (10,000-15,000 words). Written feedback will be offered by the examiners.

Learning Outcomes

Knowledge Level	Thinking Skill	Outcome
Conceptual	Understand	Synthesize and interpret current scientific knowledge of planetary systems and data science tools within the wider context of the solar system and exoplanetary research.
Procedural	Analyse	Apply appropriate statistical, machine learning, and computational modelling tools to process, analyse, and interpret large-scale planetary datasets.
Procedural	Create	Plan, conduct, and communicate a research project that combines planetary science questions with data-driven methodologies, adhering to ethical, professional, and reproducible research practices.

Oral Exam

Assessment Type	Summative	Weighting	20
Assessment Weeks	5	Feedback Weeks	7	Look up Week Numbers
Feedback	30-minute oral exam. Written feedback will be offered by the examiners.

Learning Outcomes

Knowledge Level	Thinking Skill	Outcome
Conceptual	Understand	Synthesize and interpret current scientific knowledge of planetary systems and data science tools within the wider context of the solar system and exoplanetary research.
Procedural	Create	Plan, conduct, and communicate a research project that combines planetary science questions with data-driven methodologies, adhering to ethical, professional, and reproducible research practices.
Reflection	Create	Present complex quantitative and scientific information to specialist and non-specialist audiences using written and oral communication, demonstrating advanced data interpretation skills.

Project Plan

Assessment Type	Summative	Weighting	10
Assessment Weeks	48	Feedback Weeks	50	Look up Week Numbers
Feedback	Project Plan (750-1,000 words) worth 10% of the overall grade. Written feedback will be offered by the examiners.

Learning Outcomes

Knowledge Level	Thinking Skill	Outcome
Conceptual	Understand	Synthesize and interpret current scientific knowledge of planetary systems and data science tools within the wider context of the solar system and exoplanetary research.
Procedural	Create	Plan, conduct, and communicate a research project that combines planetary science questions with data-driven methodologies, adhering to ethical, professional, and reproducible research practices.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Resubmission of failed element(s)

Assessment Type	Summative	Weighting
Assessment Weeks		Feedback Weeks	Look up Week Numbers
Feedback

Learning Outcomes

Sorry, we don't have this information available just now. Please check the course guide on or with the Course Coordinator
Knowledge Level	Thinking Skill	Outcome

Course Learning Outcomes

Knowledge Level	Thinking Skill	Outcome
Conceptual	Understand	Synthesize and interpret current scientific knowledge of planetary systems and data science tools within the wider context of the solar system and exoplanetary research.
Procedural	Analyse	Apply appropriate statistical, machine learning, and computational modelling tools to process, analyse, and interpret large-scale planetary datasets.
Procedural	Create	Plan, conduct, and communicate a research project that combines planetary science questions with data-driven methodologies, adhering to ethical, professional, and reproducible research practices.
Reflection	Create	Present complex quantitative and scientific information to specialist and non-specialist audiences using written and oral communication, demonstrating advanced data interpretation skills.

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