Python for Decision Makers and Business Leaders Transcripts
Chapter: Welcome to the course
Lecture: What we are going to cover

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0:00 Let's spend a minute and talk about the details
0:02 of what we're going to cover in this course.
0:05 We're going to start out by talking about
0:06 what you can build with Python
0:08 and we're going to look at it from two perspectives.
0:11 What are the general types of applications
0:13 that you could build with Python
0:14 say, machine learning and artificial intelligence
0:17 and what are some concrete things
0:19 people have built with Python
0:21 companies that you probably know.
0:23 I think it's very compelling to see
0:24 a company in your industry has been successful with Python.
0:28 That could help make the decision that yeah
0:30 maybe that's working out.
0:31 We're going to see that Python means three things
0:34 not just one.
0:35 It's a language, it's a set of libraries
0:37 and it's an entire ecosystem
0:39 and it's important to identify which you're talking about
0:43 when you're speaking with somebody
0:44 comparing another technology. If you say
0:47 I think the Javascript language does this
0:49 and the Python language does that,
0:51 you need to know what they're talking about.
0:53 If they say, Should we adopt Python?
0:54 I heard it's really fast.
0:56 Well, what does that mean?
0:58 Does that mean it's computational fast?
1:00 It's fast to market?
1:01 It's got a lot of libraries so we can build things quickly?
1:05 What does it mean, right?
1:06 So knowing the three things
1:07 that people talk about when they say Python
1:09 and being able to identify which those are
1:12 really helps with the conversation.
1:14 Then we're going to dig into a couple specific technologies.
1:17 We'll start with web development.
1:19 Python is great for web development.
1:20 There's a bunch of options there.
1:22 So we're going to go and check out
1:23 some Python web apps and frameworks
1:25 help you decide is that the right one for you
1:27 is that the right space at all for you
1:28 and if it is
1:29 which of the Python frameworks are good choices.
1:32 Data science is probably the place
1:34 where Python has the biggest lead over other technologies
1:38 so we're of course going to spend a little time
1:39 talking about data science and Python.
1:41 Also see that Python is really good at testing
1:44 not just testing Python code
1:46 but testing hardware testing other languages
1:49 so we're going to talk a little bit about testing with Python.
1:52 And then we're going to compare it
1:53 against other similar ecosystems
1:55 Python versus, say, .NET. How do these compare?
1:59 What are the advantages of .NET over Python
2:01 and what are the advantages of Python over .NET?
2:03 And .NET, by the way
2:05 is probably a fairly decent stand-in for Java.
2:07 They kind of play in the same space.
2:09 I know Java developers are not necessarily .NET developers
2:12 but the capabilities of those two
2:14 are pretty similar these days.
2:16 In the scientific computing world
2:18 MATLAB is really important.
2:19 Python has been making big inroads into that community.
2:23 Should you use some proprietary thing like MATLAB
2:25 or some open source thing like Python?
2:27 We'll talk about that.
2:28 And finally, Python with C++
2:30 not necessarily versus. So you might decide
2:33 should I use Python or should I use C++
2:36 or should I use them together?
2:37 They actually go together pretty well.
2:39 If you're going to switch to Python
2:41 you need to know that you can hire developers.
2:43 It's one thing to have a really cool language.
2:45 It's another to be able to say
2:47 and there's a bunch of people I can just reach out
2:49 to work with on this. Can I find consultants?
2:52 Can I find capable full-time employees, maybe co-founders?
2:55 Whatever it is that you need
2:57 knowing whether or not the job market
2:59 and the number of developers out there
3:01 is a good fit for what you're going to need
3:02 well, we're going to talk about that.
3:04 And finally, we're going to finish talking about
3:07 you've seen all this amazing stuff in Python
3:09 but when not to Python. Yeah, I'm making it a verb.
3:12 There are some areas and some situations
3:14 where it doesn't make much sense to use Python.
3:17 We'll talk about that at the end of the course.
3:18 And that's it. This is what we're going to cover.
3:21 It's going to give you a really great broad view
3:23 of the Python ecosystem.