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SPEAKER: So the tracks
that is mentioned on CS50x

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is mostly on web development,
games, iOS, Android, et cetera.

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So for someone like me that is in
the health and biology industry,

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I really want to know which other
courses I can take and develop

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my knowledge based upon them.

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So if there any advice on that,
I would really appreciate it.

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DAVID MALAN: Yeah, absolutely.

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I think that's a good problem
to have that you're so

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passionate about two different fields.

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I would recognize that first.

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I don't think you should worry as
much about pursuing a computer science

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degree solely for the purpose of
getting a job in the tech industry.

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There is certainly so
much demand right now

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for technologists that simply having
a strong technical background I

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do think will help open doors already.

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In terms of types of
courses to take, I think

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a course like CS50 that's an
introduction to procedural programming

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is compelling.

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Another course that's very popular
out there is this one here from MIT,

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called 6001, which you might
find of interest as well,

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which focuses on Python.

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The algorithms class that I mentioned
earlier I think is a good way of--

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and there's two parts to it.

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Let me go ahead and paste
both URLs, one and two--

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I think is a good way,
especially for industry,

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to get better at algorithms and
data structures more generally.

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And then I would also recommend a course
on functional programming specifically,

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which is a different type of
programming than we teach in CS50,

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and I think that will help
round out your knowledge.

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Brian, do you perhaps
have any recommendations

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along those lines or others?

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BRIAN YU: Yeah, I would agree
with all recommendations.

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In addition to that, for
biology specifically,

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and for bioinformatics in particular,
I think a course on data science

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is going to be especially helpful.

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A lot of what you'll do in data science
are going to be tools that are related

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to computer science but will
specifically help with a lot of what

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bioinformatics is all about,
which is, in large part,

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about looking at a lot
of data, whether it's--

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SPEAKER: A lot of genetics.

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BRIAN YU: Yeah, exactly.

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A lot of genetic data.

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And to that extent, I'd
also suggest maybe a course

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on artificial intelligence too.

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If you think about a
lot of the problems in--

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

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so I'm--

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BRIAN YU: Oh, I'm glad.

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Yeah, a lot of the problems--

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SPEAKER: Really happy about that.

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Thank you.

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BRIAN YU: I'm glad.

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A lot of the problems in
bioinformatics, things

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like when you're trying to do
evolutionary biology analysis,

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trying to look at how evolution
has happened, that's often done--

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SPEAKER: [INAUDIBLE]

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BRIAN YU: --machine
learning techniques too.

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Yeah, exactly.

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So--

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SPEAKER: Thank you.

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BRIAN YU: --a lot of
AI and machine learning

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can be applied to biology
and bioinformatics now too.

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SPEAKER: Thank you very much.

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I really appreciate.

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