本帖最后由 L 于 2012-12-28 23:27 编辑
首先，爱丁堡大学Informatics专业采用学分制，一共三个学期，每学期60学分，共180学分。前两个学期为授课制，第三个学期进行毕业设计和论文。
每门课学为10分或20分，如没有特别说明，大多数课程都是10分的。毕业设计为60学分。
除了下文罗列的课程，每个学生要修20学分的Informatics Research Review（第一学期）和20学分的Informatics Research Proposal（第二学期）的课，是对将来学术研究的方法进行科学指导。此外，每个学生要修一门程序设计课程，大部分方向修Introduction to Java Programming，少数方向修其他编程语言课。
总结起来如下：
1、分别在第一学期和第二学期选择IRR和IRP，各占20学分
2、从规定的专业领域内选择至少50学分的课
3、可以从其他领域选择课程至总共120学分，包括编程语言课
4、第三学期完成毕业设计60学分
下面介绍Informatics Msc专业的可选方向。
在专业设置上，爱丁堡大学信息学院Msc分为人工智能（AI）、认知科学（CG）、计算机科学（CS）和信息学（Inf）几个专业。其中前三个专业每个都有不同的方向可以选择，而Informatics专业的方向包含了前三个的所有方向，可以说是对之前的综合。
详细来说，Informatics专业方向分为：
1、应用数据库方向Analytical & Scientific Databases（CS）
2、生物信息方向Bioinformatics, Systems & Synthetic Biology
3、认知科学方向Cognitive Science（CG）
4、软件工程方向Computer Systems, Software Engineering & High-Performance Computing（CS）
5、智能机器人方向Intelligent Robotics（AI）
6、知识管理方向Knowledge Management, Representation & Reasoning（AI）
7、数据挖掘方向Learning from Data（AI）
8、自然语言处理方向Natural Language Processing（AI）（CG）
9、神经信息学方向Neural Computation & Neuroinformatics（CG）
10、理论计算机科学方向Theoretical Computer Science （CS）
每个方向后面括号中的缩写表示它也属于该专业方向。
需要解释的是，本来Informatics还可以选信息经济学、音乐信息学等特有方向，不知道为什么今年取消了，只剩下生物信息苦苦支撑。
下面介绍每个方向的课程。
Analytical & Scientific Databases（CS）
方向介绍：This specialist area brings together topics in advanced database design, theory and implementation that will be applicable to the applied as well as the research fields. There are two central academic outcomes to this programme. The first is to bring the students up to speed with the latest technology in Database Science and in the analysis of complex databases. The second aim is to introduce the students to the research active areas in the field within the context of a range of real example programmes.
该方向核心课程有两门：Advanced Databases和Querying and Storing XML
其他可选专业课有：
Data Integration and Exchange
Bioinformatics 1
Introductory Applied Machine Learning
Probabilistic Modelling and Reasoning
Extreme Computing
Bioinformatics 2
Topics in Distributed Systems
Bioinformatics, Systems & Synthetic Biology
方向介绍：The aim of the bioinformatics and synthetic biology specialist area is to familiarise students with biological data, their storage and analysis, how they integrate at a systems level, how this is studied, modelled and the emerging field of synthetic biology where biological components and systems can be constructed from first principles. In particular, students should understand what information can be extracted from biological data (e.g., information related to phylogenetic trees, biological networks, protein structure and function, developmental processes, genetic correlates of disease, etc.) and what techniques can be used for extracting and modelling such information. Students who complete the course will be prepared for employment in the bioinformatics sector of pharmaceutical and biotech industries or for entry into a PhD programme.
核心课程：Bioinformatics 1和Bioinformatics 2
可选课程：
Data Mining and Exploration
Introductory Applied Machine Learning
Machine Learning and Pattern Recognition
Models and Languages for Computational Systems Biology
Neural Computation
Performance Modelling
Probabilistic Modelling and Reasoning
Reinforcement Learning
Cognitive Science（CG）
方向介绍：The Cognitive Science specialist area gives students an opportunity to study the structure and behaviour of both natural and artificial cognitive systems. Relevant cognitive processes include language, reasoning, vision, and learning, which can be studied from neural, probabilistic, and symbolic viewpoints. Students are encouraged to also take courses from the School of Philosophy, Psychology and Language Sciences (PPLS); see the optional external courses list below.
核心课程：Computational Cognitive Science和Topics in Cognitive Modelling
可选课程：
Advanced Natural Language Processing
Advanced Vision
Automated Reasoning
Computational Cognitive Neuroscience
Human-Computer Interaction
Introductory Applied Machine Learning
Introduction to Vision and Robotics
Machine Learning and Pattern Recognition
Natural Language Generation
Neural Computation
Neural Information Processing
其他领域可选课程：
Computer Programming for Speech and Language Processing
Concepts and Categorisation
First Language Acquisition
Introduction to Mind Language and Embodied Cognition
Language Production
Multivariate Statistics and Methodology using R
Psycholinguistics
Sentence Comprehension
Simulating Language
Theories of Mind (20 points)
Univariate Statistics and Methodology Using R
Visual Word Recognition
Visual Attention
Visual Memory
Computer Systems, Software Engineering & High-Performance Computing（CS）
方向介绍：This specialist area embraces both the theory and the practice of designing programmable systems, with topics ranging from advanced programming concepts to the design of computer systems and software engineering. As with other specialist areas, this Computer Systems, Software Engineering & High-Performance Computing prepares students for Ph.D. study and for careers in the software industry. Students registered in this Specialist Area must select at least 50 credit points from the following courses, including any compulsory courses.
核心课程：无
可选课程：
Advanced Databases
Compiler Optimisation
Computer Graphics
Computer Networking
Design and Analysis of Parallel Algorithms
Distributed Systems
Extreme Computing
Human-Computer Interaction
Parallel Architectures
Parallel Programming Languages and Semantics
Performance Modelling
Software Architecture Process and Management
Software Engineering with Objects and Components
Software Testing
其他领域可选课程：
Advanced Parallel Programming
Message-Passing Programming
Parallel Design Patterns
Parallel Programming Languages
Parallel Numerical Algorithms
Performance Programming
Threaded Programming
Intelligent Robotics（AI）
游客，本帖隐藏的内容需要积分高于 100 才可浏览，您当前积分为 0
核心课程：Robotics: Science and Systems (20 points, compulsory)
可选课程：
Advanced Vision
Algorithmic Game Theory and its Applications
Computer Animation and Visualisation
Computer Graphics
Decision Making in Robots and Autonomous Agents
Information Theory
Introductory Applied Machine Learning
Machine Learning and Pattern Recognition
Probabilistic Modelling and Reasoning
Reinforcement Learning
Robot Learning and Sensorimotor Control
Knowledge Management, Representation & Reasoning（AI）
游客，本帖隐藏的内容需要积分高于 100 才可浏览，您当前积分为 0
核心课程：Automated Reasoning、Logic Programming和Multi-agent Semantic Web Systems
可选课程：
Agent Based Systems
Data Integration and Exchange
Human-Computer Interaction
Introductory Applied Machine Learning
Probabilistic Modelling and Reasoning
Software Architecture and Process Management
Topics in Cognitive Modelling
Learning from Data（AI）
方向介绍：Increasing amounts of data are being captured, stored and made available electronically. The aim of the Learning from Data specialist area is to train students in techniques to analyze, interpret and exploit such data, and to understand when particular methods are suitable and/or applicable. These techniques derive from disciplines such as machine learning, probabilistic and statistical modelling, pattern recognition and neural networks, and are sometimes collectively referred to as data mining. The specialist area will prepare students for entry into PhD programmes or for employment in commercial environments and/or scientific/engineering research.
核心课程：Machine Learning and Pattern Recognition和Probabilistic Modelling and Reasoning
可选课程：
Advanced Vision
Computer Animation and Visualisation
Data Mining and Exploration
Decision Making in Robots and Autonomous Agents
Information Theory
Introductory Applied Machine Learning
Neural Information Processing
Reinforcement Learning
Text Technologies
Natural Language Processing（AI/CG）
方向介绍：The aim of the Natural Language Processing specialist area is to prepare students for entry into PhD programmes or for employment in industrial laboratories undertaking research and development in natural language and speech processing. In this specialist area, the programming requirement should be fulfilled by taking Computer Programming for Speech and Language Processing. Students are encouraged to also take courses in speech processing or psycholinguistics in the School of Philosophy, Psychology and Language Sciences (PPLS); see the optional external courses list below.
核心课程：Advanced Natural Language Processing (20pts)和Introductory Applied Machine Learning
可选课程：
Automatic Speech Recognition
Machine Learning and Pattern Recognition
Machine Translation
Natural Language Generation
Text Technologies
其他领域可选课程：
Computer Programming for Speech and Language Processing (LEL)
Dialogue (Psychology)
Discourse Comprehension (Psychology)
Language Production (Psychology)
Multivariate Statistics and Methodology using R (Psychology)
Pragmatics (LEL)
Prosody (LEL)
Psycholinguistics (LEL)
Sentence Comprehension (Psychology)
Speech Processing (LEL)
Speech Synthesis (LEL)
Univariate Statistics and Methodology using R (Psychology)
Visual Word Recognition (Psychology)
Neural Computation & Neuroinformatics（CG）
方向介绍：This specialist area prepares students for entry into Ph.D. programmes or for employment as research workers at the intersection of the study of the brain and the study of its computation. It ranges from the study of cellular and subcellular computational processes through behavioural processes, to software methodologies for brain research - the emerging field of Neuroinformatics. In particular, students will be well prepared by this specialism to apply for entry to the School's Neuroinformatics Doctoral Training Centre.
核心课程：Neural Computation
可选课程;
Bioinformatics 1
Bioinformatics 2
Computational Cognitive Neuroscience
Computational Neuroscience of Vision
Informatics Research Methodologies
Information Theory
Neural Information Processing
Probabilistic Modelling and Reasoning
Reinforcement Learning
Topics in Cognitive Modelling
其他领域可选课程：
Statistical and Experimental Design
Theoretical Computer Science（CS）
方向介绍：The primary aims of the theoretical courses are to introduce students to core areas of theoretical Computer Science, to provide practical experience of that theory and to introduce students to the technologies through which theory-based tools are implemented, including preparation for Ph.D. study. The courses offered combine a good grounding in the core areas of the subject with experience in the practical application of theory across a range of theory-based Software Engineering tools. These courses will be of particular interest to students with a mathematics background. The practical components of these courses will consider both the use and implementation of tools. Each of the courses in this specialist area aims to provide a balance between theoretical topics and their application in software development. In many of the courses the theory suggests the construction of tools to aid software production. Students will meet a variety of these tools during the course and will have the opportunity to develop skills in their use as well as studying the techniques used in their implementation.
核心课程：无
可选课程：
Algorithmic Game Theory and its Applications
Algorithms and Data Structures
Automated Reasoning
Communication and Concurrency
Computational Complexity
Computer Algebra
Data Integration and Exchange
Information Theory
Language Semantics and Implementation
Logic Programming
Models and Languages for Computational Systems Biology
Performance Modelling
Probabilistic Modelling and Reasoning
Querying and Storing XML
Randomness and Computation
由以上可以看出来，很多课程在不同的方向中都同时出现的，说明方向之间彼此联系紧密，当然，不同方向之间的特点也体现在彼此不同的课程上。
方向及课程信息来源：
http://www.inf.ed.ac.uk/student- ... ts/specialist-areas
信息学院课程列表：
http://www.inf.ed.ac.uk/cgi-bin/dotable?numcols=8,9&file=/teaching/courses/courses12.txt&fix=2
课程书单：
http://www.inf.ed.ac.uk/admin/ITO/booklist.html
以上信息均来自2012/2013届数据。
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发表于 2012-12-29 00:16:47
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发表于 2012-12-29 00:20:49
