All language subtitles for 8. Why So Many Languages

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These are the user uploaded subtitles that are being translated: 1 00:00:01,210 --> 00:00:01,720 Welcome back. 2 00:00:02,440 --> 00:00:09,010 I wanted to answer this question that I get a lot of even from professional developers that have been 3 00:00:09,010 --> 00:00:10,120 in the field for years. 4 00:00:10,120 --> 00:00:14,100 So I want to tackle this question really quickly right now. 5 00:00:14,230 --> 00:00:16,720 Why are there so many programming languages. 6 00:00:16,750 --> 00:00:21,970 Why can we just have one language that does everything and everybody's happy and we don't have to worry 7 00:00:21,970 --> 00:00:25,880 about learning so many programming languages. 8 00:00:25,960 --> 00:00:33,520 And here's the thing in your career you don't need to know five 10 eight languages now you can be a 9 00:00:33,520 --> 00:00:40,930 really successful developer programmer with just want language just finding that speciality of yours 10 00:00:41,770 --> 00:00:48,220 and programming languages like Python Java and JavaScript offer a lot of opportunities where you don't 11 00:00:48,220 --> 00:00:49,750 need to learn another language. 12 00:00:50,080 --> 00:00:52,620 But why are there so many languages. 13 00:00:52,810 --> 00:00:57,760 If we go to Wikipedia These are the list of programming languages. 14 00:00:57,910 --> 00:01:04,240 And if you're looking through here you should be intimidated because there's no way in your lifetime 15 00:01:04,300 --> 00:01:12,400 you're going to learn all of these and while you won't most likely you're going to learn one two maybe 16 00:01:12,400 --> 00:01:20,870 three languages in your entire lifespan or career as a programmer and different programming languages 17 00:01:20,930 --> 00:01:22,700 are good for different things. 18 00:01:22,700 --> 00:01:27,190 Just like we have different tools to let's say build a house. 19 00:01:27,320 --> 00:01:31,910 You can't just build a house with a hammer you need different tools that are good at different things 20 00:01:31,910 --> 00:01:34,170 to assemble what you want. 21 00:01:34,220 --> 00:01:40,790 So it's impossible to build one ultimate language when we have so many applications so many mobile phones 22 00:01:40,790 --> 00:01:45,200 so many computers so many devices like cameras. 23 00:01:45,200 --> 00:01:52,160 So you have low level languages that we've talked about like assembly code or C and then we have higher 24 00:01:52,160 --> 00:01:55,070 level languages like Python and JavaScript. 25 00:01:55,070 --> 00:02:06,350 Now here's the thing python is usually slower than languages like C++ or C sharp or even Java and we 26 00:02:06,350 --> 00:02:11,030 don't need to get into technical details here but I do want to tell you about a tradeoff. 27 00:02:11,420 --> 00:02:18,140 You see you don't really want to write Python code for low level systems and hardware interactions. 28 00:02:18,170 --> 00:02:22,970 If you're taking this course while you're probably not even interested in that field you see Python 29 00:02:23,390 --> 00:02:29,340 although slower than some languages is good at one thing and does this really really well. 30 00:02:29,720 --> 00:02:38,480 That is developer productivity because python is so easy to learn or at least is very similar to the 31 00:02:38,480 --> 00:02:39,770 English language. 32 00:02:40,010 --> 00:02:45,980 It's become really really popular for developers to be productive and write code really really fast 33 00:02:46,010 --> 00:02:53,870 and less lines than something like C so A print Hello World for example in Python would take while just 34 00:02:53,870 --> 00:02:58,260 one line but all languages have their different strength. 35 00:02:58,280 --> 00:03:02,710 For example if you want to build an app on Android or an OS device. 36 00:03:02,990 --> 00:03:08,600 Well you're not really going to use Python but if you want to do machine learning maybe you want to 37 00:03:09,020 --> 00:03:16,580 build a web server maybe you want to do data visualizations build scripts that process thousands of 38 00:03:16,580 --> 00:03:17,570 Excel files. 39 00:03:17,600 --> 00:03:22,760 Well in that case you're going to use Python and we're going to cover what different things you can 40 00:03:22,760 --> 00:03:25,580 do with Python and what Python is really really good at. 41 00:03:25,730 --> 00:03:29,630 In this course as we explore different projects later on. 42 00:03:29,630 --> 00:03:31,460 But keep that in mind. 43 00:03:31,460 --> 00:03:37,760 The reason there's so many programming languages is that every programming language excels at some things 44 00:03:38,090 --> 00:03:42,190 and while doesn't do so well at others it's all about tradeoff. 45 00:03:42,200 --> 00:03:44,010 There is no ultimate language. 46 00:03:44,150 --> 00:03:49,970 And if a programmer tells you you hate my language is the best language they're probably junior developers 47 00:03:49,970 --> 00:03:51,290 that don't know what they're talking about. 48 00:03:51,470 --> 00:03:56,270 Everything is a pro and con everything has a tradeoff. 49 00:03:56,270 --> 00:04:04,490 And as programmers what really good senior programmers do is being able to detect what these pros and 50 00:04:04,490 --> 00:04:10,760 cons are and what tool to use for a specific problem something that throughout this course I'm going 51 00:04:10,760 --> 00:04:11,960 to try and teach. 52 00:04:12,110 --> 00:04:13,560 I'll see you in the next one. 53 00:04:13,760 --> 00:04:13,950 Bob. 5713

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