Overview
We will start by discussing the type of data to be analysed. A part from typical single number time series such as temperatures or stock prices, we will also consider the evolution of geospatial variables, 3D and text data.
This will be followed by the some basic Exploratory Data Analysis in the context of time dependent data.
The Time Dependent Data: from Financial Analytics to Large Language Models course from Queen Mary University of London will then provide insights on how time dependent data can be analysed based on real world examples and applications. Areas of applications that might be considered are speech, stock market evolution, music, geospatial data such as MRI scans, and medical time series data used in diagnostics.
Key Facts
- Introduce students to the fundamental concepts of time-dependent data analysis in financial markets, medicine, social studies and other domains.
- Develop a basic understanding of the methodologies and tools used to analyze time series data.
- Provide hands-on experience with real-world datasets to apply theoretical concepts.
- Explore the application of time-dependent data analysis in the context of large language models and cognitive sciences.
- Equip students with the skills to critically evaluate and interpret dynamic data trends in various fields.
Programme Structure
You will develop/be able to:
- analyse and interpret time dependent data Analysis
- consider and evaluate models used in the analysis of time dependent data
- utilise existing and new analytical and computational techniques in the resolution of real life problems related to the field
Key information
Duration
- Full-time
- 19 days
Start dates & application deadlines
- Starting
- Apply before
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Language
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Credits
Delivered
Disciplines
Computer Sciences Data Science & Big Data Data Analytics View 35 other Short Courses in Data Analytics in United KingdomWhat students do after studying
Academic requirements
English requirements
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Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
Get your student insurance nowStarting from €0.53/day, free cancellation any time.
Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at Queen Mary University of London and/or in United Kingdom, please visit Student Insurance Portal.
Other requirements
General requirements
We accept a range of qualifications:
- if your home institution uses the four-point Grade Point Average (GPA) scale, we usually require a 3.0 GPA
- if your home institution uses the letter scale, you will need to have a B+
- if your home university uses the UK scale, we require a 2:1 average
- if your home university uses a percentage scale, we usually require a minimum 65% average
- If you hold a degree from a majority English speaking country plus Canada you may use this degree to satisfy the English language requirements for entry, provided the degree was completed no more than 5 years before the start date of the course to which you are applying.
- An IELTS score of 7 or higher, for the majority of courses
- An IELTS score of 6.5 or higher for science-based courses
- A TOEFL iBT score of 92 or higher
- CET4 - 550 or CET 6 - 493
- A degree taught in English within the last five years*
Tuition Fee
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International
2500 GBP/yearTuition FeeBased on the tuition of 2500 GBP per year during 19 days. -
National
2500 GBP/yearTuition FeeBased on the tuition of 2500 GBP per year during 19 days.
If you choose to study for 2 sessions you automatically receive a tuition fee discount
- One Session £2500
- Both Sessions £4900
Living costs for London
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.