WEBVTT 00:00.570 --> 00:01.560 Hello. 00:01.560 --> 00:07.620 I'm super excited to start this course with you, but before we do, we need to see where we're starting 00:07.620 --> 00:11.910 and where we're ending up so we have a clear path to success. 00:12.240 --> 00:19.410 Now, this course has over 200 HD videos and tons of exercises and projects, but they're all broken 00:19.410 --> 00:22.710 down into sections to help us learn better. 00:22.800 --> 00:27.240 The course is going to start off with Python basics in here. 00:27.240 --> 00:32.310 If this is your first time learning a programming language, it's going to be super, super helpful, 00:32.310 --> 00:37.590 even for those that know a programming language already but don't know anything about Python. 00:37.590 --> 00:43.950 This section is going to get to cut up to speed with the basics so that you feel comfortable programming. 00:43.950 --> 00:50.010 This is a big section, so we actually have two parts and along the way you're going to watch me code, 00:50.010 --> 00:56.910 but also code yourself and practice coding so that you get comfortable with what Python has to offer 00:57.210 --> 00:57.960 next. 00:57.960 --> 01:01.410 We talk about a professional Python developer environment. 01:01.500 --> 01:07.530 We teach you how to use the terminal and the command line about using code editors like Sublime Text 01:07.530 --> 01:08.910 and Visual Studio code. 01:08.940 --> 01:16.440 We talk about using Pi Charm, a fully integrated IDE for Python developers, and also how to use Jupyter 01:16.440 --> 01:17.160 Notebooks. 01:17.160 --> 01:22.650 Because we're going to use these notebooks later on in the course to do something really, really exciting. 01:22.650 --> 01:24.270 Hint, hint, it's machine learning. 01:24.270 --> 01:31.080 And once we have a fully professional developer environment, we then get into some advanced Python 01:31.080 --> 01:31.860 topics. 01:31.860 --> 01:36.750 Now this section, we're not going to shy away from any tough topics, but I'm going to help you understand 01:36.750 --> 01:38.340 them and make sense of it all. 01:38.340 --> 01:44.730 We're going to talk about classes, object oriented programming, about decorators, generators, error 01:44.730 --> 01:51.600 handling, functional programming as well as best practices when it comes to how to write clean code. 01:51.930 --> 01:58.230 And we'll also learn about popular Python packages, how to work with files, how to test our code, 01:58.260 --> 02:01.320 how to use regular expressions, and so much more. 02:01.350 --> 02:05.880 Your head might hurt by the end of this section, but trust me, it's going to be fun now. 02:05.880 --> 02:08.100 Most courses will be done by then. 02:08.100 --> 02:12.090 You've learned Python and you should be all set, right? 02:12.240 --> 02:19.320 Well, not really, because once we've learned this new language, this new syntax, we have our computers 02:19.320 --> 02:20.850 set up to work with Python. 02:20.850 --> 02:24.450 We need to talk about how we can apply our newfound knowledge. 02:24.450 --> 02:26.610 This is the fun part of the course. 02:26.700 --> 02:30.810 We start talking about the careers and the career options you have in Python. 02:30.810 --> 02:33.660 Then we get into different fields that we can use. 02:33.660 --> 02:34.110 Python. 02:34.230 --> 02:40.140 We're going to learn about scripting in Python, where we use Python to send automated emails. 02:40.140 --> 02:47.790 We use Python to process images, work with PDF files, we use Python to send ourselves text messages. 02:47.790 --> 02:49.500 We build a Twitter bot. 02:49.500 --> 02:56.070 And my favorite project in this section is we build a password checker to actually see if the passwords 02:56.070 --> 02:58.380 that you use have ever been hacked. 02:58.380 --> 03:00.030 It's a really, really fun one. 03:00.150 --> 03:02.730 We also talk about data scraping. 03:02.730 --> 03:10.140 A very common use case with Python is to scrape data from online and use it for something productive. 03:10.140 --> 03:15.750 In our case, we're going to learn about data scraping and how we can scrape a really popular website 03:15.750 --> 03:22.230 for programmers to only select the articles that are important for you to stay up to date with the industry 03:22.230 --> 03:22.710 again. 03:22.710 --> 03:24.420 It's going to be a really fun project. 03:24.420 --> 03:27.690 I know I'm saying all projects are fun, but I'm biased. 03:27.690 --> 03:28.740 Give me a break here. 03:28.770 --> 03:34.230 We're also going to learn about automation and we're going to use something called selenium to actually 03:34.230 --> 03:41.880 control through our machines a web browser and get the machine to do different tasks as if it's a user. 03:41.880 --> 03:46.320 And there's some really fun applications when it comes to automation that we'll talk about. 03:46.320 --> 03:53.370 And then I know, I know everybody's two favorite topics web development and data science and machine 03:53.370 --> 03:53.940 learning. 03:54.390 --> 03:59.580 These two sections are going to be a ton of fun and I think are going to probably be the most popular 03:59.580 --> 04:01.530 sections in the web development section. 04:01.530 --> 04:09.600 We're going to learn how to use HTML, CSS and JavaScript as well as Python to build our own server, 04:09.600 --> 04:16.890 build our own portfolio website, put the website online in production, and have future employers and 04:16.890 --> 04:19.260 customers message you through your website. 04:19.380 --> 04:24.510 And yes, you're going to get to customize it and do whatever you want to this portfolio website so 04:24.510 --> 04:26.910 you have something to show for it at the end of the course. 04:26.910 --> 04:32.460 And then the machine learning data science part, we're going to use something called Jupyter Notebooks 04:32.460 --> 04:36.750 and Kaggle to access some really interesting data sets. 04:36.750 --> 04:42.510 We're going to use libraries like pandas and psych and learn to predict which soccer players are going 04:42.510 --> 04:45.570 to be the most valuable or are underpaid. 04:45.600 --> 04:51.630 We're going to build our own machine learning model using the iris data set, and then we're also going 04:51.630 --> 04:57.510 to do some image detection where we can feed the machine learning model an image, and it's going to 04:57.510 --> 04:59.400 predict what the image is of. 04:59.730 --> 05:05.550 And you're actually going to see how this magic of machine learning works underneath the hood. 05:05.760 --> 05:11.250 As you can see, we have a ton to cover in this course, and by the end of it all, this is all going 05:11.250 --> 05:17.730 to fit in together and make sense from the very beginning of Python basics to the very end with machine 05:17.730 --> 05:18.190 learning. 05:18.210 --> 05:20.730 We're going to take you from zero to mastery. 05:21.090 --> 05:24.090 But you know what the best part of this course is? 05:24.090 --> 05:25.430 Our online community. 05:25.440 --> 05:31.740 We have thousands of developers chatting every day, helping each other out, solving problems together, 05:31.740 --> 05:35.080 and just talking about the latest and greatest in programming. 05:35.100 --> 05:40.230 Now, this is an optional resource for you to use, so you can have back and forth conversations with 05:40.230 --> 05:41.790 other students and myself. 05:41.790 --> 05:45.990 So you feel like you're part of a classroom and you're not doing this all alone. 05:46.200 --> 05:47.100 But you know what? 05:47.100 --> 05:48.000 Enough talk. 05:48.000 --> 05:49.380 I know you're getting excited. 05:49.380 --> 05:50.100 I am, too. 05:50.130 --> 05:51.360 So let's get started. 05:51.360 --> 05:56.910 Let's start learning and see why Python has become the most popular language in the world.