MSc Advanced Computer Science Module Choices
Yesterday I chose which modules I wanted to take throughout my time here at The University of York whilst studying for my MSc in Advanced Computer Science.
Our course consists of 80 credits of taught content over two terms, delivered in 8 modules worth 10 credits each, and 100 credits worth of research project (known as the Project for Advanced Computer Science or PACS for short) over the summer term and the long vacation.
At York modules are taught in blocks of four weeks, each term consisting of two four-week blocks and a ‘free’ week between them. Assessments are taken at the end of each four week block.
Term 1 (October – December)
Evolutionary Computation (EVCO)
This module covers genetic algorithms, genetic programming, evolutionary strategies, and co-evolutionary frameworks, in other words any computer algorithms or systems that are inspired by natural evolutionary systems.
Model-Driven Engineering (MODE)
MODE will introduce the theory, principles and practices of model-driven engineering.
Concurrent & Real-Time Programming (CRTP)
The CRTP module will have us using the Real-Time Specification for Java to develop real-time embedded systems.
Constraint Programming (COPR)
Constraint Programming tackles problems such as timetabling, scheduling, allocation, planning, configuration, layout and routing — such problems are known as finite-domain constraint satisfaction problems (FD-CSPs) and require a different approach to other problems due to the large search spaces they can create.
We will use a language called MiniZinc to meta-program a set of constraints for problems to be solved.
Quantum Computation (QUCO)
QC provides an introduction to the cutting-edge world of Quantum Computation and will explain the promises and limitations of its usage as well as some of the algorithms expected to gain performance or indeed only be possible on quantum computers.
Term 2 (January – March)
Quantum Information Processing (QIPR)
Quantum information processing takes off where the quantum computing module finishes and introduces the theories of quantum communication (which could guarantee against snooping), provides more information about the qubit, and explains the weird effect of quantum teleportation.
Adaptive and Learning Agents (ALAS)
ALAS is and artificial intelligence module which covers both machine learning and intelligent agents.
Static Analysis and Verification (SAVE)
This module covers the use of state-of-the-art techniques for verification of object-oriented programs. As with all of the modules taught at York this is in Java.
I’m really looking forward to studying all of the modules listed, particularly Evolutionary Computation, Concurrent & Real-Time Programming and both Quantum modules. The block 1 modules start on Monday 6th October, just 4 days time. I can’t wait. 🙂