Iain Robinson - Education
My
chosen degree programme placed great emphasis on providing
students with both theoretical understanding and practical
experience of the majority of the topics covered. As a result I
was able to develop my existing programming skills and gain
experience of new programming languages. I learned to work well in
teams and individually, to devise creative solutions to problems.
I improved my ability to present ideas and work (both verbally and
on paper) and, through ongoing assessment,
to work to strict deadlines.
The degree concentrated on the fields of computer
science and AI in equal measure. Modules related to the computer
science aspect provided me with a good overall understanding of
the design, construction and operation of computer hardware,
operating systems, software and networks while modules relating to
AI complemented these by examining all areas of work carried out
in the field of AI/ALife.
The following is an outline of the topics covered by the course:
| Year 1 |
| Data Structures |
| Foundation & Further Artificial Intelligence |
| Foundations of Computer Science |
| Foundation & Further Programming |
| Introduction to Logic |
| Mathematical Tools for Cognitive Scientists |
| Software Design |
| Technical Communication Skills |
|
| Year 2 |
| Algorithmics |
| Computer Systems Architecture |
| Computer Vision |
| Functional Programming |
| Introduction to Operating Systems |
| Languages & Compilers |
| Multimedia Communications Technology |
| Non-Symbolic Artificial Intelligence |
| Software Engineering |
| Symbolic Artificial Intelligence |
|
| Year 3 |
| Adaptive Systems |
| Animal & Machine Intelligence |
| Data Mining |
| Distributed Systems |
| Internet Technologies |
| Space Systems |
|
The course was divided into two main topics:
- Knowledge Based Systems - introduced the concepts and
applications of rules and the handling of uncertainty in KBSs
with particular reference to Bayesian updating, certainty theory
and fuzzy logic.
- Artificial Neural Networks - focused on the
practical applications and underlying mechanisms of single and
multi-layer perceptrons, Hopfield networks and Kohonen networks.