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Overview
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 and Machine Learning - The Fundamentals 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.
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.
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Visit programme websiteProgramme Structure
The course will cover a number of topics, including:
- Data Science and Machine Learning: motivating successful analytic examples (Walmart, Google, and Twitter), introducing Supervised, Unsupervised, and Reinforcement Learning, measuring performance / regret, fundamental limits (the No-Free-Lunch-Theorem and Bias);
- Probability recap, e.g., sample spaces, random variables, distributions, heavy-tails, quantiles, Q-Q plots, Bayes, correlation;
- Statistics recap, e.g., hypothesis testing, chi-square distributions, density estimation (MoM and MLEs), confidence intervals and application to voting;
- Stochastic bandits as a fundamental example of Reinforcement Learning: naïve Explore-then-Exploit strategy and UCB bounds;
Audience
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Visit programme websiteKey information
Duration
- Full-time
- 15 days
Start dates & application deadlines
- Starting
- Apply before
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Language
English
Credits
3 alternative credits
3-4 credits (US) 7.5 ECTS points (EU)
Delivered
On Campus
Disciplines
Data Science & Big Data Machine Learning View 37 other Short Courses in Machine Learning in United KingdomExplore more key information
Visit programme websiteAcademic 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.
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
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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.
Make sure you meet all requirements
Visit programme websiteTuition Fee
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-
International
3150 GBP/fullTuition FeeBased on the tuition of 3150 GBP for the full programme during 15 days. -
National
3150 GBP/fullTuition FeeBased on the tuition of 3150 GBP for the full programme during 15 days.
For any students in full-time education at any University or College worldwide: £2350
Living costs for Coventry
656 - 1057 GBP /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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