项目背景
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更新时间:2024-07-08
开学时间9月
课程学制1年
学费29900.00/GBP
专业介绍
Computational Mathematics, in particular the physical applied areas and the theory and implementation of numerical methods and algorithms, have wide-ranging applications in both the public and private sectors. More recently, in this era of ubiquitous and cheap computing power, there has been an explosion in the number of problems that require us to understand processes by modelling them, and to use data sets that are large. The subject of Computational Mathematics has become increasingly prominent. There is high demand also for computational modellers and data scientists. This programme concentrates on the overlap and synergy between these fields.
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6
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总分
6.5
92
62
学术要求
专业领域：numerate类专业如数学、工程学、计算机科学、物理或生物科学、经济学或商学。 科目：足够的数学科目微积分（包括多变量微积分）、线性代数、概率论、统计学和统计理论。
课程设置
Compulsory couses 必修课 Numerical Linear Algebra：数值线性代数 Applied Dynamical Systems：应用动力系统 Python Programming：Python编程 Numerical Partial Differential Equations：数值偏微分方程 Research Skills for Computational Applied Mathematics：计算应用数学的研究技能 Dissertation (CAM)：论文 (CAM) Optional courses 选修课 Statistical Methodology：统计方法 Introductory Probability and ：介绍性概率和 Applied Stochastic Differential Equations：应用随机微分方程 Stochastic Modelling：随机建模 Fundamentals of Optimization：优化基础 Statistical Programming：统计规划 Bayesian Theory：贝叶斯理论 Industrial Mathematics：工业数学 Data Analytics with High Performance Computing：具有高性能计算的数据分析 Numerical Ordinary Differential Equations and Applications：数值常微分方程及其应用 Time Series：时间序列 Large Scale Optimization for Data Science：数据科学的大规模优化 Optimization Methods in Finance：金融中的优化方法 Bayesian Data Analysis：贝叶斯数据分析 Mathematics in Action A：行动中的数学A Machine Learning in Python：Python中的机器学习 Numerical Methods for Data：数据的数值方法 Uncertainty Quantification：不确定性量化 Nonlinear Optimization：非线性优化
OfferEasy/找专业/ 英国数学/统计/运筹/ 爱丁堡大学计算应用数学专业
