Open University

BSc (Honours) in Data Science

Knowledge and understanding

On completion of this degree, you will have knowledge and understanding of:

• A range of simple and more advanced methods for analyzing statistical data (including medical applications data, time series data, and multivariate data), working with statistical models, and carrying out statistical inference (including in particular methods for linear and generalized linear models, and Bayesian methods)
• Calculus, differential equations, linear algebra, multivariable calculus, and vector calculus
• The fundamental principles, concepts, and techniques underlying computing and IT, and the range of models used to support the analysis and design of computing and IT systems
• The range of situations in which computing and IT systems are used in data science and the possibilities and limitations of such systems
• Machine learning and artificial intelligence
• The ethical and legal issues associated with data science
• A selection (depending on your options) of advanced topics including advanced data management and analysis, graph theory, network analysis, mathematical methods, applied probability, mathematical statistics, and interactive design.

Cognitive skills

On completion of this degree, you will be able to:

• Use your judgement in applying and selecting a wide range of mathematics and statistics tools and techniques to solve real-world problems
• Construct appropriate mathematical and statistical models and draw justifiable inferences in qualitative and quantitative problem-solving skills
• Reason with abstract concepts
• Apply and critically evaluate key computing and IT concepts in a range of contexts
• Select and apply appropriate techniques and tools for abstracting, modelling, problem-solving, designing and testing computing and IT systems, and be aware of the limitations involved.

Practical and professional skills

On completion of this degree, you will be able to:

• De is an independent learner, able to acquire further knowledge with minimal guidance or support
• Use appropriate professional tools, including programming languages, to support your work
• Apply mathematical, statistical and computational concepts, principles and methods
• Analyse and evaluate problems and plan strategies for their solution
• Analyse, design, evaluate and/or test models and systems, using appropriate simulation and modelling tools as appropriate
• Identify and address the ethical, social and legal issues that may arise during the development and use of computing and IT systems.

Key skills

On completion of this degree, you will be able to demonstrate the following skills:

• Communicate information, arguments, ideas and issues clearly and in appropriate ways, bearing in mind the audience for and the purpose of the communication
• Find, assess and apply information from a variety of sources, using information technology where appropriate
• Select, and use accurately, appropriate numerical and analytical techniques to solve problems
• Prepare mathematical, statistical and computational content for a range of purposes, which may include writing for both specialist and non-specialist audiences
• Recognise and understand a range of technological and practical problems and select suitable techniques for solving them.

This degree has three stages, each comprising 120 credits.

• In Stage 1, you’ll study four 30-credit modules.
• In Stage 2, you’ll study four 30-credit modules.
• 在第 3 阶段，您将学习两个 30 学分的模块并选择两个 30 学分的选修模块。

Stage 1 (120 credits)

您将学习以下所有四部分：

• 统计学入门（M140）
• 计算机与信息技术简介 1 (TM111)
• Essential Mathematics 1 (MST124)
• 计算机与信息技术简介 2 (TM112)

Stage 2 (120 credits)

您将学习以下所有四部分：

• 分析数据 (M248)
• 算法、数据结构和可计算性（M269）
• Mathematical Methods (MST224)
• 实用现代统计学（M249）

Stage 3 (120 credits)

You'll study both of the following:

• 应用统计建模（M348）
• 机器学习与人工智能（TM358）

此外，您还可以从以下选项中选择两个：

• 概率的应用（M343）
• Computational Applied Mathematics (MST374)
• 数据管理和分析（TM351）
• 图表、游戏和设计 (MST368)
• 交互设计和用户体验（TM356）
• 数理统计（M347）

Assessment

Our assessments are all designed to reinforce your learning and help you show your understanding of the topics. The mix of assessment methods will vary between modules.

Computer-Marked Assignments

• Usually, a series of online, multiple-choice questions.

Tutor-Marked Assignments

• You’ll have a number of these throughout each module, each with a submission deadline.
• They can be made up of essays, questions, experiments or something else to test your understanding of what you have learned.
• Your tutor will mark and return them to you with detailed feedback.

End-of-Module Assessments

• The final, marked piece of work on most modules.
• Modules with an end-of-module assessment won’t usually have an exam.

Exams

• Some modules end with an exam. You’ll be given time to revise and prepare.
• You’ll be given your exam date at least 5 months in advance.
• Most exams take place remotely, and you will complete them at home or an alternative location.
• If a module requires you to take a face-to-face exam, this will be made clear in the module description, and you will be required to take your exam in person at one of our exam centres.

职业发展技能

分析复杂数据集的能力是现代职场中备受追捧的技能。该学位将为您提供统计学、应用数学和计算机科学的数据分析和建模知识。此外，您还将培养重要的可转移技能，例如沟通、时间管理和解决问题。

职业相关性

几乎所有工作场所都对数据科学家的需求都很大。社交媒体、在线商务和政府部门对数据科学的使用彻底改变了数字经济，公共和私营部门的雇主现在都在招聘数据科学家来识别和解决复杂的业务问题。数据科学家是支持战略和运营决策的核心。商业智能、管理、生物学、经济学、教育、工程、环境研究、金融、政府、物流、医学、气象学、市场研究、体育和跨国企业等所有就业领域都需要他们。

通过我们独特的远程学习方法，您可以在家中、在工作中或在旅途中学习。

你需要满足一些评估截止日期，但除此之外，你可以自由地在适合自己的时间学习，将学习安排在工作、家庭和社交生活之间。

对于每个模块，您要么只使用在线资源，要么结合使用在线和印刷材料。

您学习的每个模块都会有一个模块网站

• 每周的学习计划，为你提供循序渐进的学习指导
• 课程材料，如阅读材料、视频、录音和自我评估活动
• 用于与其他学生进行讨论和合作活动的模块论坛
• 每项作业的详细信息及其截止日期
• 辅导预订系统、在线辅导室以及导师的联系方式
• 一些印刷模块材料和资源的在线版本。