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