Last modified: 08 Dec 2023 13:16
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.
| Study Type | Undergraduate | Level | 2 |
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| Session | Second Sub Session | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | Yes |
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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.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 60 | |
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| Assessment Weeks | Feedback Weeks | |||
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Topics include applications of data analytics and machine learning, green finance and FINTECH (word limit: 2000). |
Word Count | 2000 | |
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| Assessment Type | Summative | Weighting | 40 | |
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| Assessment Weeks | Feedback Weeks | |||
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Students have the chance to develop their own Python code and demonstrate its application in data analytics and machine learning. |
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There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
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| Assessment Weeks | Feedback Weeks | |||
| Feedback |
2,000 words |
Word Count | 2000 | |
| Knowledge Level | Thinking Skill | Outcome |
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| Knowledge Level | Thinking Skill | Outcome |
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| Factual | Remember | Not Available |
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