Introduction - What to Expect From the Course

Quick reference

• 00:05 All right, welcome to the course.
• 00:06 My name is John Elder and I'll be your instructor today.
• 00:08 In this video, I want to spend just a couple of minutes talking
• 00:11 about what you can expect from the course, how we're going to move forward, and
• 00:14 give you a basic roadmap that we're going to follow throughout the course.
• 00:18 So this course is basically broken down into five main sections.
• 00:21 And in the first section, we're going to download and
• 00:24 install most of the tools that we need for the course.
• 00:27 Now there will be some things we need to install as we go on from time to time, and
• 00:30 we'll do that, but
• 00:31 the first section is where we're going to download the main tools that we need.
• 00:34 So we'll start out by downloading this terminal.
• 00:36 This is the Git Bash terminal.
• 00:38 It will allow us to run certain commands that we need to run from time to time.
• 00:42 It will also allow us to download and install other things behind the scenes.
• 00:46 Once we download the Git Bash terminal, we'll download Python itself so
• 00:49 we can actually use Python throughout the course and
• 00:52 then we'll set up a virtual environment where we can download and
• 00:55 install other things, other modules, throughout the course.
• 00:58 After that, we'll set up Jupyter Notebooks and this is Jupyter Notebooks, it's a web
• 01:02 browser-based program that allows us to run Python right in the web browser and
• 01:07 do all of our data analysis.
• 01:10 So those are the main tools that we're going to need.
• 01:12 None of them cost any money, they're all free and open source.
• 01:15 So, as long as you have internet access, you can download and install those.
• 01:18 After that we'll jump into NumPy.
• 01:20 Now NumPy stands for Numerical Python and it does a lot of the math
• 01:24 behind the scenes that we're going to be doing throughout the course.
• 01:26 And NumPy is not very flashy but it's very important for data analysis.
• 01:31 So we're not going to spend a whole lot of time on it but
• 01:33 you need a fundamental understanding of certain concepts with NumPy.
• 01:37 We'll look at NumPy arrays, NumPy operations, and
• 01:40 NumPy universal functions and you can start to see some of these right here.
• 01:45 After that, we'll look at pandas and pandas is a lot of fun,
• 01:48 it allows for visualization of data.
• 01:51 So when you think of pandas, think of Excel spreadsheets.
• 01:54 See right here, this is a pandas data frame.
• 01:57 So we'll start out that section learning about pandas series,
• 02:00 but we'll spend most of that section looking at data frames and
• 02:03 learning about how to use them and do certain things with them.
• 02:06 In the next section, we'll look at pandas visualization.
• 02:09 We'll learn how to create all kinds of charts and graphs.
• 02:11 This is a fun section, it's very visual.
• 02:14 You can see before this we're dealing with lots of numbers, in this section,
• 02:18 we're going to be looking at charts and graphs and
• 02:19 you can see right here, we're going to do histograms.
• 02:22 We're going to do area plots.
• 02:24 We're going to do bar charts, bar graphs, some line graphs, some scatter plots,
• 02:29 some box plots.
• 02:30 All the fun charts and
• 02:31 graphs that you're going to want to learn how to use, we'll look at in that section.
• 02:34 After that, we'll finish up the course by spending a little bit of time
• 02:37 learning about some basic machine learning.
• 02:39 Now, there is just vast amounts of machine learning stuff that we can learn and
• 02:44 this course is primarily about data analysis but
• 02:46 we're going to learn how to create a linear regression model.
• 02:49 And we're going to use some historic housing data from Boston in order to run
• 02:53 a linear regression analysis.
• 02:55 As you can see right here, also do some charts and graphs and things like that and
• 02:59 it's a lot of fun.
• 03:00 So I'm really looking forward to this course.
• 03:02 I hope you are too.
• 03:04 We're going to learn a lot of stuff.
• 03:05 We're going to learn it very fast.
• 03:06 And I think you're going to be surprised just how quick and easy it is
• 03:09 to pick up a lot of this stuff, even though it's a fairly complicated topic.
• 03:13 Hopefully we can break it down into nice little chunks that are easy to digest.
• 03:17 So let's get started.

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