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MSc Data Science
在愛丁堡大學
關於課程
Data science is the study of the computational principles, methods, and systems for extracting and structuring knowledge from data, and the application and use of those principles. Large data sets are now generated by almost every activity in science, society, and commerce - ranging from molecular biology to social media, from sustainable energy to health care.
As an MSc Data Science student, you will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem:
Machine learning focuses on finding patterns and making predictions from data.
Ideas from algorithms and databases are required to build systems that scale to big data streams.
Separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.
As an MSc Data Science student, you will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem:
Machine learning focuses on finding patterns and making predictions from data.
Ideas from algorithms and databases are required to build systems that scale to big data streams.
Separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.
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開始日期及學費
如何申請
Entry requirements for 愛丁堡大學
A UK 2:1 honours degree, or its international equivalent, in informatics, artificial intelligence, cognitive science, computer science, electrical engineering, linguistics, mathematics, philosophy, physics, psychology or another quantitative discipline. Entry to this programme is competitive. A typical offer will normally require a UK first class honours degree. You should have experience of computer programming equivalent to an introductory programming course and have completed the equivalent to 60 credits of mathematics during your degree that have typically covered the following subjects/topics: calculus (differentiation and integration), linear algebra (vectors and multi-dimensional matrices), discrete mathematics and mathematical reasoning (e.g. induction and reasoning, graph theoretic models, proofs), and probability (concepts in discrete and continuous probabilities, Markov chains etc.)
IELTS Academic: total 6.5 with at least 6.0 in each component
TOEFL-iBT: total 92 with at least 20 in each section.
English language requirements
托福(TOEFL iBT)總分: 100.0
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