Warwick Summer School: Data Science and Machine Learning: The Fundamentals
31 May, 2026Application Deadline
JulStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
Other
Study Level
Masters
Study Mode
On Campus
The most important aspect of computer science is problem solving, an essential skill for life.
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 parallel, Machine Learning is concerned with the development of analytical models and algorithms to learn from data and make accurate predictions.
This course addresses fundamental aspects of Data Science and Machine Learning, e.g., analytical models to represent and understand the data, efficient algorithms to manipulate and extract relevant knowledge, and corresponding models to understand their overall performance and limitations.
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 course, 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.
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 parallel, Machine Learning is concerned with the development of analytical models and algorithms to learn from data and make accurate predictions.
This course addresses fundamental aspects of Data Science and Machine Learning, e.g., analytical models to represent and understand the data, efficient algorithms to manipulate and extract relevant knowledge, and corresponding models to understand their overall performance and limitations.
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 course, 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.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
Other
Study Level
Masters
Study Mode
On Campus
The most important aspect of computer science is problem solving, an essential skill for life.
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 parallel, Machine Learning is concerned with the development of analytical models and algorithms to learn from data and make accurate predictions.
This course addresses fundamental aspects of Data Science and Machine Learning, e.g., analytical models to represent and understand the data, efficient algorithms to manipulate and extract relevant knowledge, and corresponding models to understand their overall performance and limitations.
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 course, 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.
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 parallel, Machine Learning is concerned with the development of analytical models and algorithms to learn from data and make accurate predictions.
This course addresses fundamental aspects of Data Science and Machine Learning, e.g., analytical models to represent and understand the data, efficient algorithms to manipulate and extract relevant knowledge, and corresponding models to understand their overall performance and limitations.
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 course, 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.
Admission Requirements
130+
100+
7+
70+
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. Our Summer School courses are taught in English so students must be able to demonstrate a good level of English language and comprehension. We assess students' English ability through their application and correspondence.
31 May 2026
Jul
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