Methods Related Lecture Courses

Apart from the [:MachineLearning:Learning Machine Learning] course and the course [http://www.mrc-cbu.cam.ac.uk/research/seminars/statisticsseminars.html Statistical Methods for Cognitive Psycologists] there are other useful courses from the Engineering Department, Centre of Mathematical Sciences and Computer Laboratory.

==Engineering Department 2008==

• Michaelmas Module 3F1 – Signals and Systems

  http://www.eng.cam.ac.uk/teaching/courses/y3/3f1.html Module 3G4 - Medical Imaging and 3-D Computer Graphics

  http://www.eng.cam.ac.uk/teaching/courses/y3/3g4.html Module 4M13 -Complex Analysis and Optimization

  http://www.eng.cam.ac.uk/teaching/courses/y4/4m13.html Module 4F6 - Signal Detection and Estimation (Fitzgerald)

  http://www.eng.cam.ac.uk/teaching/courses/y4/4f6.html Module 4F10 - Statistical Pattern Processing

  http://www.eng.cam.ac.uk/teaching/courses/y4/4f10.html Module 4F7 - Digital Filters andSpectrum Estimation

  http://www.eng.cam.ac.uk/teaching/courses/y4/4f7.html Module 4G3 - Computational Neuroscience

  http://www.eng.cam.ac.uk/teaching/courses/y4/4g3.html

The timetables are available

• Lent Module 3D7 - Finite Element Methods

  http://www.eng.cam.ac.uk/teaching/courses/y3/3d7.html

  Module 3F2 – Systems & Control http://www.eng.cam.ac.uk/teaching/courses/y3/3f2.html

  Module 3F3 – Signal & Pattern Processing http://www.eng.cam.ac.uk/teaching/courses/y3/3f3.html Module 4M12 - Partial Differential Equations and Variational Methods

  http://www.eng.cam.ac.uk/teaching/courses/y4/4m12.html Module 3G3 Introduction to Neuroscience

  http://www.eng.cam.ac.uk/teaching/courses/y3/3g3.html Module 3F6 – Software Engineering and Design

  http://www.eng.cam.ac.uk/teaching/courses/y3/3f6.html Module 5R1 - Stochastic Processes and Optimization Methods

  http://www.eng.cam.ac.uk/teaching/courses/y4/5r1.html Basic Maths from the Engineering Department Michaelmas Mathematics Part IA (1st Year)

  http://www.eng.cam.ac.uk/teaching/courses/y1/P4-MM.html Centre of Mathematical Studies Statistical Laboratory CMS M.Phil in Statistical Science

  http://www.statslab.cam.ac.uk/Postgrad/MPhil/mphilinfo08.html Lent Term Applied Bayesian Statistics Prof. D. Spiegelhalter M.W. 11, MR14 and CATAM room (eleven lectures and five classes) • Bayes theorem; principles of Bayesian reasoning • Exact conjugate analysis • Assessment of prior distributions • Monte Carlo analysis • Markov chain Monte Carlo methods • Regression analysis (linear, glm, nonlinear) • Model criticism and comparison • Hierarchical models (glmms) The practical classes will use WinBUGS. Time Series+ Lent DR S. M. Pitts Tu. Th. S. 12 MR9 (first eight lectures) Monte Carlo Inference+ Lent DR R.R. Gramacy Tu. Th. S. 12 MR9 Lent (last sixteen lectures) M. Phil in Computational Biology at CMS Computational Neuroscience Lent DR S. Eglen Tu. Th. 12 MR 15

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