So I'm in my second set of courses in my master's program, and I still have a lot to learn.
Let me set the stage a bit: last post I mentioned that I have two bachelor's degrees, with one in Psychology and one in Fine Arts, emphasis in animation. While they were interesting programs, they were not directly computer science related. For obvious reasons, this presents a little bit of a hurdle when it comes to studying artificial intelligence.
That isn't to say I'm completely up a creek without a paddle. Animation required a decent amount of computer-knowledge in order to work through various programs and applications, and I've taken a few online computer science and programming courses on my own through University of the People. Thankfully, the program at Utrecht University also has a strong emphasis on psychology and cognitive modeling (compared to many other graduate-level AI programs I looked at), so I'm not the only one without a strong CS background.
But I would like to know more. There's a lot of really interesting things going on the CS side that I feel like I don't fully grasp, and the process of discovering where the holes in my knowledge are is a bit daunting. That, in turn, makes the process of filling those gaps seem overwhelming. The technical nature of the field is not the easiest for me to digest--I find science to be something I'm very compelled towards, but maths and languages..not so much. Learning and internalizing those subjects takes a lot of time, and I feel a little bit like I'm rewiring my brain...but it's very satisfying when I come to understand a process or concept.
In concrete terms, I want to better learn the programming language Python, and then maybe later C++ (I am interested in gaming and its application beyond entertainment, so that would be useful). I think some greater understanding of algorithms, evolutionary computing, data mining, and neural networks would be highly useful, but I'm not sure I have the basis to learn these topics well quite yet. In all cases, I find learning the theory alone to be insufficient in feeling competent in the subjects--I'm looking for practical application, practice and deeper understanding. This makes the task a fair bit harder, given that I'm not quite sure where even to begin gaining a better understanding on my own. My thought right now is to find some personal projects or exercises to dive into Python with, but even that seems like a pretty big pool of possibilities.
But, I'll do my best.
Right now, we're working with the language R in a course on cognitive modeling. It's fairly new to me, but not overly complicated...however, there's a lot I'm not familiar with yet. My lab partner is a guy out of Slovenia, and he has a background in CS with some experience in R, so that has been a huge help. I'm doing what I can to learn as well though, since there's not much to gain in letting someone else do all the work for you (especially when you're paying the tuition for it). Hopefully, though, learning some R will help me pick up on the brainspace necessary for tackling other programming languages as well.
Let me set the stage a bit: last post I mentioned that I have two bachelor's degrees, with one in Psychology and one in Fine Arts, emphasis in animation. While they were interesting programs, they were not directly computer science related. For obvious reasons, this presents a little bit of a hurdle when it comes to studying artificial intelligence.
That isn't to say I'm completely up a creek without a paddle. Animation required a decent amount of computer-knowledge in order to work through various programs and applications, and I've taken a few online computer science and programming courses on my own through University of the People. Thankfully, the program at Utrecht University also has a strong emphasis on psychology and cognitive modeling (compared to many other graduate-level AI programs I looked at), so I'm not the only one without a strong CS background.
But I would like to know more. There's a lot of really interesting things going on the CS side that I feel like I don't fully grasp, and the process of discovering where the holes in my knowledge are is a bit daunting. That, in turn, makes the process of filling those gaps seem overwhelming. The technical nature of the field is not the easiest for me to digest--I find science to be something I'm very compelled towards, but maths and languages..not so much. Learning and internalizing those subjects takes a lot of time, and I feel a little bit like I'm rewiring my brain...but it's very satisfying when I come to understand a process or concept.
In concrete terms, I want to better learn the programming language Python, and then maybe later C++ (I am interested in gaming and its application beyond entertainment, so that would be useful). I think some greater understanding of algorithms, evolutionary computing, data mining, and neural networks would be highly useful, but I'm not sure I have the basis to learn these topics well quite yet. In all cases, I find learning the theory alone to be insufficient in feeling competent in the subjects--I'm looking for practical application, practice and deeper understanding. This makes the task a fair bit harder, given that I'm not quite sure where even to begin gaining a better understanding on my own. My thought right now is to find some personal projects or exercises to dive into Python with, but even that seems like a pretty big pool of possibilities.
But, I'll do my best.
Right now, we're working with the language R in a course on cognitive modeling. It's fairly new to me, but not overly complicated...however, there's a lot I'm not familiar with yet. My lab partner is a guy out of Slovenia, and he has a background in CS with some experience in R, so that has been a huge help. I'm doing what I can to learn as well though, since there's not much to gain in letting someone else do all the work for you (especially when you're paying the tuition for it). Hopefully, though, learning some R will help me pick up on the brainspace necessary for tackling other programming languages as well.
