WEBVTT 00:00:00.087 --> 00:00:02.406 If you’re working as a computer scientist, 00:00:02.406 --> 00:00:04.977 no matter whether it’s in computational biology, 00:00:04.977 --> 00:00:08.361 finance, logistics, or even the secret service, 00:00:08.361 --> 00:00:09.561 chances are 00:00:09.561 --> 00:00:10.721 that you’ll come across 00:00:10.721 --> 00:00:12.505 very tough problems that can only be 00:00:12.505 --> 00:00:14.970 solved by a computer. Or so you might 00:00:14.970 --> 00:00:16.890 think because here’s the bad news: 00:00:17.090 --> 00:00:18.843 There are literally thousands 00:00:18.843 --> 00:00:20.543 of problems out there 00:00:20.543 --> 00:00:22.214 for which you might think that it’s 00:00:22.214 --> 00:00:23.934 simple for a computer to solve them 00:00:23.934 --> 00:00:25.456 but it’s actually very hard, 00:00:25.456 --> 00:00:26.813 if not downright impossible. 00:00:26.813 --> 00:00:28.973 This course introduces you to theoretical 00:00:28.973 --> 00:00:31.265 computer science, the area of computer science 00:00:31.265 --> 00:00:33.936 that deals with very hard problems. 00:00:33.936 --> 00:00:35.738 And I think that even if you plan to 00:00:35.738 --> 00:00:38.003 become a very practical computer scientist, 00:00:38.113 --> 00:00:40.837 it’s vital that you know about those theoretical concepts 00:00:40.897 --> 00:00:42.600 Plus, we will also encounter some 00:00:42.600 --> 00:00:44.607 really fascinating and mind boggling 00:00:44.607 --> 00:00:46.650 results from theoretical computer science, 00:00:46.650 --> 00:00:49.158 such as deceptively simple problems that 00:00:49.158 --> 00:00:51.500 no computer will ever be able to solve. 00:00:51.820 --> 00:00:54.500 So I’m happy to invite you to take this journey 00:00:54.500 --> 00:00:57.400 into the science of challenging problems.