Computer Laboratory

Course pages 2015–16

Topical Issues

Overview

Topical Issues is a fairly unique course within the CS Tripos. It is intended to broaden horizons and to provide basic grounding in some hot topics in the industry. This means that the lectures are often standalone rather than being a flowing series, and the list of topics covered often changes to track current trends. Where possible, guest lecturers are used to get expert views.

There are two exam questions on the course in Part II, although many students attend for interest rather than with the intention of doing the questions in the exams. Students are welcome to attend only a subset of the lectures.

Lecture Plan

The plan below is subject to change as the availability of guest lecturers can fluctuate at short notice.

F22/04/16Course intro, the Internet of ThingsRobert Harle
M25/04/16Deep Belief Networks for Speech at GoogleMatt Stuttle & David Singleton, Google
W27/04/16AlphaGoGeorge van den Driessche, DeepMind/Google
F29/04/16UWB RadioAndy Ward, Ubisense
M02/05/16Getting Location for Mobile DevicesRobert Harle
W04/05/16Sensor Fusion TechniquesRobert Harle
F06/05/16Autonomous VehiclesRobert Harle
M09/05/16Introduction to Bluetooth Low Energy (BLE)Robin Heydon, CSR
W11/05/16Bluetooth MeshRobin Heydon, CSR
F13/05/16The Road to Autonomous DrivingAlan Jones, Cotares
M16/05/16RFID and NFCRobert Harle
W18/05/16No lecture
Please note that the last lecture will be on Monday 16th May and not Wednesday.

Examples Sheet

First sheet is available here Second sheet is available here

Materials

The lecture slides are available via Raven. Please do not distribute them beyond the University (guest lecturers have not given permission for this)
Lecture 1: Intro and IoT
Lecture 2: Speech Recognition (Machine Learning) at Google
Lecture 3: AlphaGo
Lecture 4: UWB
Lecture 5: Location for Mobile Devices
Lecture 6: Sensor Fusion Techniques
Lecture 7: Autonomous Vehicles
Lecture 8: Bluetooth Low Energy
Lecture 9: Bluetooth Mesh
Lecture 10: The Road To Autonomous Vehicles
Lecture 11: RFID