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CDT Taught Modules

Taught Courses

Researchers at Robotics Week

In the first year of their study, students will take around fifteen graduate courses which will span the first two terms. Each module will typically take 1-2 weeks, with the weekly schedule consisting of lectures each morning with hands-on experience in the afternoons to enable consolidation of theory. Each module will emphasise case examples from a breadth of application domains.

Those modules will be:

  • Data Estimation and Inference
  • Signal Processing
  • Machine Learning
  • Optimisation
  • Embedded Systems Programming
  • Introduction to Modern Control
  • Discriminative & Deep Learning for Big Data
  • Computer Vision
  • Systems Verification
  • Security in Wireless and Mobile Networks
  • Computational Game Theory
  • Deep Learning in Distributed & Constrained Systems
  • Autonomous Systems Safety & Governance
  • Reinforcement Learning
  • Internet of Things
  • Autonomous Robotics