Overview
Data Science is concerned with how to gain knowledge from the vast volumes of data generated daily in modern life, from social networks to scientific research and finance, and proposes sophisticated computing techniques for processing this deluge of information.
In particular, students study the design, development and analysis of software and hardware used to solve problems in a variety of business, scientific and social contexts. During this Data Science - Foundations of Data Analytics at the University of Warwick, students will study techniques for how to go from raw data to a deeper understanding of the patterns and structures within the data, to support making predictions and decision making. Students would be expected to have some basic knowledge of linear algebra and calculus.
Course Aims
To understand the foundational skills in data analytics, including preparing and working with data; abstracting and modelling an analytic question; and using tools from statistics, learning and mining to address the question.
Learning Outcomes
By the end of the module, the student should be able to:
- Understand the basic mathematical models for large data sets.
- Understand the principles and purposes of data analytics, and articulate the different dimensions of the area.
- Work with and manipulate a data set to extract statistics and features, coping with missing and dirty data.
- Apply basic data mining machine learning techniques to build a classifier or regression model, and predict values for new examples.
Programme Structure
The course will cover a number of topics, including:
- Basic tools: command line tools, plotting tools, programming tools
- Statistics: Probability recap, distributions, significance tests, R
- Regression: linear regression, least squares, logistic regression
- Matrices: Linear Algebra, SVD, PCA - Matrices to represent relations between data, and necessary linear algebraic operations on matrices.
- Clustering: hierarchical, k-means, k-center - Finding clusters in data via different approaches. Choosing distance metrics.
Audience
Key information
Duration
- Full-time
- 3 days
Start dates & application deadlines
- Starting
- Apply before
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- Students and those not requiring immigration permissions can apply after the 31st May if our courses are not yet full.
Language
Credits
3-4 credits (US) 7.5 ECTS points (EU)*
Delivered
Disciplines
Data Science & Big Data Data Analytics View 38 other Short Courses in Data Analytics in United KingdomAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is open to students studying any discipline at University level provided they have basic knowledge of linear algebra and calculus.
- We welcome individuals from all backgrounds, including students who are currently studying another subject but who want to broaden their knowledge in another discipline.
- Students should also meet our standard entry requirements and must be aged 18 or over by the time the Summer School commences and have a good understanding of the English language.
Tuition Fee
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International
2350 GBP/fullTuition FeeBased on the tuition of 2350 GBP for the full programme during 3 days. -
National
2350 GBP/fullTuition FeeBased on the tuition of 2350 GBP for the full programme during 3 days.
Living costs for Coventry
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding