SPEAKER: So the tracks that is mentioned on CS50x is mostly on web development, games, iOS, Android, et cetera. So for someone like me that is in the health and biology industry, I really want to know which other courses I can take and develop my knowledge based upon them. So if there any advice on that, I would really appreciate it. 

DAVID MALAN: Yeah, absolutely. I think that's a good problem to have that you're so passionate about two different fields. I would recognize that first. I don't think you should worry as much about pursuing a computer science degree solely for the purpose of getting a job in the tech industry. There is certainly so much demand right now for technologists that simply having a strong technical background I do think will help open doors already. 

In terms of types of courses to take, I think a course like CS50 that's an introduction to procedural programming is compelling. Another course that's very popular out there is this one here from MIT, called 6001, which you might find of interest as well, which focuses on Python. The algorithms class that I mentioned earlier I think is a good way of-- and there's two parts to it. Let me go ahead and paste both URLs, one and two-- I think is a good way, especially for industry, to get better at algorithms and data structures more generally. And then I would also recommend a course on functional programming specifically, which is a different type of programming than we teach in CS50, and I think that will help round out your knowledge. Brian, do you perhaps have any recommendations along those lines or others? 

BRIAN YU: Yeah, I would agree with all recommendations. In addition to that, for biology specifically, and for bioinformatics in particular, I think a course on data science is going to be especially helpful. A lot of what you'll do in data science are going to be tools that are related to computer science but will specifically help with a lot of what bioinformatics is all about, which is, in large part, about looking at a lot of data, whether it's-- 

SPEAKER: A lot of genetics. 

BRIAN YU: Yeah, exactly. A lot of genetic data. And to that extent, I'd also suggest maybe a course on artificial intelligence too. If you think about a lot of the problems in-- 

SPEAKER: I am actually looking forward to the AI class that is coming up, so I'm-- 

BRIAN YU: Oh, I'm glad. Yeah, a lot of the problems-- 

SPEAKER: Really happy about that. Thank you. 

BRIAN YU: I'm glad. A lot of the problems in bioinformatics, things like when you're trying to do evolutionary biology analysis, trying to look at how evolution has happened, that's often done-- 

SPEAKER: [INAUDIBLE] 

BRIAN YU: --machine learning techniques too. Yeah, exactly. So-- 

SPEAKER: Thank you. 

BRIAN YU: --a lot of AI and machine learning can be applied to biology and bioinformatics now too. 

SPEAKER: Thank you very much. I really appreciate.