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CS4049: INTRODUCTION TO MACHINE LEARNING AND DATA MINING (2021-2022)

Last modified: 21 Oct 2021 17:00


Course Overview

This course provides an introduction to machine learning and data mining. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time-series analysis, neural networks, and many other techniques. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.   

Course Details

Study Type Undergraduate Level 4
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Mingjun Zhong
  • Dr Bruno Yun

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

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

This course provides an introduction to machine learning and data mining. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time-series analysis, neural networks, and many other techniques. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future. 

Content:  

Obtaining, preparing, managing, and presenting data 

Supervised learning, classification, regression 

Unsupervised learning, clustering 

Decision-tree learning 

Neural networks and deep learning 

Case-studies and applications 


In light of Covid-19 this information is indicative and may be subject to change.

Contact Teaching Time

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

Teaching Breakdown

  • 1 Practical during University weeks 10 - 19

More Information about Week Numbers


Summative Assessments

Computer Programming Exercise

Assessment Type Summative Weighting 30
Assessment Weeks 17 Feedback Weeks 18

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Written Feedback

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralAnalyseAbility to identify, prepare, and manage appropriate datasets for analysis.
ProceduralEvaluateKnowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done.
ProceduralEvaluateAbility to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context.

Computer Programming Exercise

Assessment Type Summative Weighting 30
Assessment Weeks 12 Feedback Weeks 14

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Written Feedback

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralAnalyseAbility to identify, prepare, and manage appropriate datasets for analysis.
ProceduralEvaluateAbility to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context.
ProceduralEvaluateKnowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done.

Exam

Assessment Type Summative Weighting 40
Assessment Weeks Feedback Weeks

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To take place in May

Learning Outcomes
Knowledge LevelThinking SkillOutcome
ProceduralAnalyseAbility to identify, prepare, and manage appropriate datasets for analysis.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Resubmission of failed elements

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

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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
ProceduralEvaluateAbility to analyse the results of data analyses, and to evaluate the performance of analytic techniques in context.
ProceduralEvaluateKnowledge and understanding of analytic techniques, and ability to appropriately apply them in context, making correct judgements about how this needs to be done.
ProceduralAnalyseAbility to identify, prepare, and manage appropriate datasets for analysis.
ProceduralCreateAbility to appropriately present the results of data analysis

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