Study information

Topics in Environmental Intelligence - 2024 entry

MODULE TITLETopics in Environmental Intelligence CREDIT VALUE15
MODULE CODEMTHM611 MODULE CONVENERDr Oscar Rodriguez De Rivera Ortega (Coordinator)
DURATION: TERM 1 2 3
DURATION: WEEKS 0 11 0
Number of Students Taking Module (anticipated) 30
DESCRIPTION - summary of the module content

This module offers an insight to cutting-edge applications of Environmental Intelligence. You will be taught by world-leading experts in the application of Data Science and Artificial Intelligence to environmental data to address important questions related to the environment.  You will have the opportunity to explore a range of topics that address some of the most important challenges facing society today, including climate change, clean air, extreme weather events and the sustainable development goals. You will learn about new, and exciting techniques, including uncertainty quantification and the use of cloud computing. The choice of topics in any year may change to ensure that the content of the module reflects the rapid change in this exciting area.

AIMS - intentions of the module

The aims are to expose you to some recent developments in environmental intelligence; to allow you to study one or more advanced topics in some depth and to gain some insight into areas of postgraduate research in statistics. The choice of topics in any year may change to ensure that the content of the module reflects the rapid change in this exciting area.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

1. Demonstrate an understanding of current developments in environmental intelligence.

2. Demonstrate an understanding of the strengths and limitations of different modelling approaches

3. Demonstrate the ability to apply advanced methodology across a variety of settings.

Discipline Specific Skills and Knowledge

4. Demonstrate an understanding the application of statistics, machine learning and AI in environmental challenges and real-world data.

5. Demonstrate the ability to self-learn further details of the methodology introduced within topics.

Personal and Key Transferable / Employment Skills and Knowledge

6. Demonstrate data analysis skills in complex topics

7. Demonstrate self-learning and making effective use of learning resources.

8. Communicate the results of a data analysis clearly and accurately, both in writing and verbally.

SYLLABUS PLAN - summary of the structure and academic content of the module
Whilst the module’s precise content may vary from year to year, an example of an overall structure is as follows:
 
  • Climate change 
  • Clean air
  • Extreme weather 
  • Natural disasters
  • Circular economy
  • Sustainable development goals
  • Clean/renewable energy 
  • Cloud computing
     
Other suitable topics may also be offered. Topics would be delivered in separate blocks, for remote delivery and mixture of lecturers, and cover the introduction/background, challenges and issues, data collection and collation, impacts and current and potential future uses of data science/statistics/machine learning/AI. 
LEARNING AND TEACHING
LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)
Scheduled Learning & Teaching Activities 30 Guided Independent Study 120 Placement / Study Abroad 0
DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS
Category Hours of study time Description
Scheduled Learning and Teaching Activities 20 Lectures
Scheduled Learning and Teaching Activities 10 Hands-on practical sessions
Guided Independent Study 56
Self-study and background reading
Guided Independent Study 64 Assessed data analyses, report writing

 

ASSESSMENT
FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade
Form of Assessment Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Feedback on unassessed problem sheets and data analyses  5 x 1 hour 1-8 Oral, in practical sessions

 

SUMMATIVE ASSESSMENT (% of credit)
Coursework 80 Written Exams 0 Practical Exams 20
DETAILS OF SUMMATIVE ASSESSMENT
Form of Assessment % of Credit Size of Assessment (e.g. duration/length) ILOs Assessed Feedback Method
Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting 80 Max 10 pages (plus appendices) 1-8 Written and oral
Individual presentation 20 Max 10 minutes 1-8 Written and oral

 

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)
Original Form of Assessment Form of Re-assessment ILOs Re-assessed Time Scale for Re-assessment
Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting (80%) 1-8 Ref/def period
Individual presentation Pre-recorded individual presentation (20%) 1-8 Ref/def period

 

RE-ASSESSMENT NOTES

For referred candidates, the mark will be capped at 50%. For deferred candidates, the mark will be uncapped. Please refer to the TQA section on Referral/Deferral: https://as.exeter.ac.uk/academic-policy-standards/tqa-manual/aph/consequenceoffailure/

RESOURCES
INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

The reading list will depend upon the module topic(s) offered and will be specified in detail by the lecturer(s) and agreed by the module coordinator for any particular year.

Reading list for this module:

There are currently no reading list entries found for this module.

CREDIT VALUE 15 ECTS VALUE 7.5
PRE-REQUISITE MODULES MTHM609, MTHM610
CO-REQUISITE MODULES
NQF LEVEL (FHEQ) 7 AVAILABLE AS DISTANCE LEARNING No
ORIGIN DATE Wednesday 12th January 2022 LAST REVISION DATE Tuesday 17th January 2023
KEY WORDS SEARCH Climate change; clean air; energy; environment

Please note that all modules are subject to change, please get in touch if you have any questions about this module.