Computer Science Honours at UCT: Part 2

This is part 2 in my review of the CS honours modules at UCT. Read after reading part 1.

Introduction to Image Processing and Computer Vision (IPCV):

I've always had a small interest in image processing, so I might be a bit biased towards this module. IPCV is lectured by Patrick and I think he does an excellent job of it. He covers topics such as image transformations, feature detection and segmentation. This was also the first of many modules in which genetic algorithms were touched on. It requires a moderate amount of mathematical background, especially linear algebra. If you're into your maths in any way I'd strongly recommend it, but if you're not I'd be cautious, but still consider it. Six of the lectures are used as paper reviews in which you read a paper before the lecture and then discuss it in class.

The assignment is all about using the Hough Transform for circle detection. For those doing the module or any other image-related programming I strongly suggest the CImg library as it has a gentle learning curve and is well documented. The assignment is a simplified version of my second year project and I plenty test data available here.

Parallel Computing (PC):

This is another module I might be a bit biased towards due to personal interest in the subject. I really enjoyed it, even though it was perhaps a little lacking in detail. PC is lectured by Michelle and covers parallel architectures and parallel programming. This year there was a big emphasis on parallel genetic algorithms.

The assignment this year (it changes every year) was to program a parallel genetic algorithm without a library. Parallel programming can be tricky, especially to debug. Added together with genetic algorithms, which can be touchy, made it a not-so trivial task.

I would strongly encourage almost anyone to take PC. It's a nice thing to know how to do parallel programming, especially with the ever increasing number of cores going onto PC processors.

Agents:

I was very excited about taking the Agents module. This was the first time we covered anything related to artificial intelligence and it was lectured by Anet who's research area is agents. It is another one of those modules that has been affected by the introduction of the gaming stream. The Intelligent Systems (IS) module was moved into the gaming stream and we lost the opportunity to take it. So for us, and hopefully the impact will be lessened next year, we had both modules squeezed into one. This resulted in a broad overview of the many AI topics without much depth. Topics covered included neural networks, genetic programming (GP) and several topics related to agents ending off with complex adaptive systems.

The assignment was to program a GP to produce a strategy for predators whose goal it was to capture a single prey. This was one of the more time-consuming assignments, however it was very enjoyable. We had to produce a report on our implementation, which you can read here. The exam is apparently the most difficult of the year and take-home exam. It is often said by ex-honours students and I agree: be scared of open book exams, be very scared of take-home exams!

Genetic Algorithms (GA):

Audrey is one of the newest lecturers in our department and with all senior lecturers required to take an honours module, she started a new one on Genetic Algorithms. I don't want to harp on this too much for her sake, but she wasn't very well prepared and the module ended up having very little content. Most of the lectures were taken by the class, including all the examinable content. Hopefully Audrey will learn from her rough ride this year.

Putting the negatives aside, the module does have a lot of potential. GA's is one of Audrey's main research areas and there's a lot to learn about them. I think some of the GA content covered by other modules needs to be removed in order for this one to become a success. This year we covered the basics of GA's, applications of GA's and GA toolkits.

We each gave a 45 minute lecture in groups of up to three, with each group covering a paper. While it was not for marks, the exam covers a selection of these papers and nothing else. The assignment was to experiment with a genetic algorithm using a GA toolkit and write a report about it. I took advantage of the similarities between this and the Agents assignment and combined them. You can read my report here.

Internet Interoperability (II):

This module is taken by Hussein and that's one of the main reasons I took the module. The other reason is our assignment was all about programming a Facebook application, with the idea being to deal with interoperability issues first hand. I wrote a whole separate post one the assignment here. The module covered several topics around interoperability such as protocols, data/metadata, repositories and web services. It was an interesting module if you're interested in the web at all, but I would give it second thoughts given the choice again.

Intra-Domain Traffic Engineering (ITE):

Of all the modules I took, but not for credit, this was my favourite. Another of our newest lecturers, Antoine, started this as a new module this year. Traffic engineering is all about how to route traffic from source to destination. While this might sound simple at first, just consider what happens when links start failing. There are some fairly complex graph theory problems introduced, such as the K-shortest path problem which tries to get K disjoint shortest paths.

Antoine covers the module at a good pace, allowing for plenty discussion. So many lecturers take their lectures in such a way that almost prevents discussion, which is a real pity when you're in a smallish class. I didn't do the assignments, but there were three of them using NS. The exam is a brief oral exam covering mainly covering the assignments.

Still one more post to come and the module reviews will be done!

Part 3