诺丁汉大学/英国

授课型硕士 · 2027

网络物理系统理学硕士

Cyber Physical Systems MSc

理学硕士MSc

学制

全日制 12 个月Full-time: 12 months

授课

全日制Full-time

学费

英镑 34,800 · UK fees: £14,600; International fees: £34,800GBP 34,800 · UK fees: £14,600; International fees: £34,800

英语

—

入学要求

2:1 (or international equivalent) with programming skills evidenced through prior study or practical experience detailed in the application.

学年课程

课程模块Modules

  • 理学硕士MSc
  • 网络安全路径Cyber Security pathway
  • 实验室评估laboratory evaluation
  • surveys
  • case studies
  • 行动研究action research
  • 广告特设网络Ad Hoc Networks
  • Mobile Ad Hoc Networks (MANETs)
  • Vehicular Ad Hoc Networks (VANETs)
  • Disconnection/Disruption/Delay Tolerant Networks (DTNs)
  • binary search trees (red-black trees)
  • 动态编程dynamic programming
  • graph-algorithms (eg shortest path, maximum flows)
  • amortized analysis
  • priority queues (binary, leftist and Fibonacci heaps)
  • string algorithms (string matching, longest common subsequence)
  • public-key cryptography (the RSA cryptosystem)
  • the page-rank algorithm (from Google search)
  • neural networks
  • 机器学习基础machine learning foundations
  • pattern recognition foundations
  • artificial neural networks
  • 深学习deep learning
  • 应用机器学习applications of machine learning
  • data mining techniques and evaluating hypotheses

必修Core modules

  • 实验室评估laboratory evaluation
  • surveys
  • case studies
  • 行动研究action research
  • 广告特设网络Ad Hoc Networks
  • Mobile Ad Hoc Networks (MANETs)
  • Vehicular Ad Hoc Networks (VANETs)
  • Disconnection/Disruption/Delay Tolerant Networks (DTNs)

选修Optional modules

  • binary search trees (red-black trees)
  • 动态编程dynamic programming
  • graph-algorithms (eg shortest path, maximum flows)
  • amortized analysis
  • priority queues (binary, leftist and Fibonacci heaps)
  • string algorithms (string matching, longest common subsequence)
  • public-key cryptography (the RSA cryptosystem)
  • the page-rank algorithm (from Google search)
  • neural networks
  • 机器学习基础machine learning foundations
  • pattern recognition foundations
  • artificial neural networks
  • 深学习deep learning
  • 应用机器学习applications of machine learning
  • data mining techniques and evaluating hypotheses

申请节点

September 2027

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