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Last modified: 05 Aug 2021 13:04

Course Overview

This course will provide an introduction to data analytics and machine learning (often summarised as Big Data) and its applications in international business. The course will explore recent trends in green finance and FINTECH, which are based on data analytics and recent advances in machine learning.

Course Details

Study Type Undergraduate Level 2
Session Second Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study Yes
  • Professor Gerhard Kling

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

What other courses must be taken with this course?


What courses cannot be taken with this course?

Are there a limited number of places available?


Course Description

The course will provide an introduction to Python, which has become the dominant general-purpose programming language in data analytics and machine learning. To be clear, students are not expected to have any prior knowledge of Python or any other programming language.

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 Seminar during University weeks 25 - 34, 38
  • 1 Tutorial during University weeks 27, 29, 31, 33

More Information about Week Numbers

In light of Covid-19 and the move to blended learning delivery the assessment information advertised for second half-session courses may be subject to change. All updates for second-half session courses will be actioned in advance of the second half-session teaching starting. Please check back regularly for updates.

Summative Assessments

2000-word Essay (60%);

Group Project (40%)


Resit (for students who took the course in Academic Year 2020/21):   

Individual essay (max 3000 words) - 100%

Resit (for students who took the course in Academic Year 2019/20 or for C8 students):   
Individual essay (max 3000 words) - 100%

Formative Assessment

There are no assessments for this course.

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
FactualRememberNot Available

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