国际学生入学条件
Candidates must have obtained at least a Second Class Honours Grade II in a primary honours degree (NFQ, Level 8) or equivalent in a numerate discipline (i.e., commensurate with science or engineering programmes).
Candidates are expected to have taken courses in mathematics, applied mathematics or statistics at university level, and be familiar with calculus, vectors, matrices and elementary statistics. They are expected to have sufficient background in university-level mathematics as assessed by the course coordinator. In the case of competition for places selection will be made on the basis of primary degree results and/or interview. For online modules, students are advised to have access to a laptop/home computer with an internet connection, modern browser, word processing and spreadsheet software.
Candidates from Grandes Écoles Colleges are also eligible to apply if they are studying a cognate discipline in an ENSEA or EFREI Graduate School and are eligible to enter the final year (M2) of their programme.
All candidates must ultimately be approved by the director of the MSc (Mathematical Modelling and Self-Learning Systems) programme.
IELTS - 6.5 Overall 6.0 Individual Skills (academic version)
TOEFL iBT - 90 Overall (Listening 20, Reading 19, Speaking 21, Writing 20)
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雅思考试总分
6.5
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雅思考试指南
- 雅思总分:6.5
- 托福网考总分:90
- 托福笔试总分:160
- 其他语言考试:PTE -Minimum score of 63 with no section score below 59.
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申请截止日期: 请与IDP顾问联系以获取详细信息。
课程简介
自学习系统是许多应用科学领域(例如应用数学)中的重要且新兴的技术
Machine learning is an important and newly emerging technique in many areas of applied science such as applied mathematics, engineering, computer science and statistics.<br><br>In particular, machine and self-learning systems are innovative approaches to mathematical modelling which use differential equations at their foundation. A particular strength of this approach is that it ultimately allows you to design applications that can adapt to a changing environment. This is a new and rapidly developing area at the interface between applied mathematics and machine learning.<br><br>The primary aim of our Mathematical Modelling programme at UCC is to provide you with training in the use and development of modern numerical methods and machine-learning software. You will develop and apply new skills to real-world problems using mathematical ideas and techniques together with software tailored for complex networks and self-learning systems. While there is a strong focus on modern applications, our graduates will gain in-demand skills in mathematical modelling, problem-solving, scientific computing, dynamic machine learning, complex networks and communication of mathematical ideas to a non-technical audience.<br>We also teach general hands-on skills such as mathematical typesetting, mathematical writing, desktop and web-based mathematical software development, and the use of computer languages and packages such as C#, R, Python and TensorFlow – all of which are highly prized by employers in this field.
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