WEBVTT 00:00.050 --> 00:02.180 Congratulations are definitely in order. 00:02.210 --> 00:06.380 Yesterday was a mammoth first day on this course and you got through it. 00:06.380 --> 00:09.560 You set up your environment and we're off to the races. 00:09.560 --> 00:14.840 So as I recap, what you can now do is use a llama to run models locally. 00:14.840 --> 00:18.410 You can call OpenAI's API to run a frontier model. 00:18.410 --> 00:22.130 You understand, at least at a high level, the difference between a system and a user prompt. 00:22.130 --> 00:28.730 And you've built a summarization use case, which is an important commercial application. 00:29.120 --> 00:35.270 Today we're going to talk a bit about what are the steps to get to being an LLM engineer, set you up 00:35.270 --> 00:39.110 for success, and then talk more about frontier models. 00:39.110 --> 00:41.030 That is the plan. 00:41.060 --> 00:47.750 Now, let me start by just emphasizing that this course, this eight week course is a practical course. 00:47.750 --> 00:50.480 First and foremost we're going to cover theory. 00:50.510 --> 00:53.420 We're going to cover the foundational information that you need. 00:53.420 --> 00:56.600 But we're always going to do it in a practical context. 00:56.630 --> 00:59.810 I'm a big believer in the best way to learn is by doing. 00:59.810 --> 01:01.640 And that's what we'll be actually doing. 01:01.820 --> 01:03.620 And we're going to be putting it to good use. 01:03.620 --> 01:06.620 We're going to be building commercial projects as we go. 01:06.620 --> 01:11.390 And I'll often be asking you to try and think about how you could apply what you've learned to your 01:11.390 --> 01:15.710 day job and try and build little prototypes to bring that to life. 01:15.710 --> 01:18.470 So that is the flavour of the course. 01:18.950 --> 01:24.740 There are three different aspects to LM engineering that you'll be picking up as we go. 01:24.770 --> 01:29.960 The first of them is just understanding the models that are out there, the wide range of different 01:29.990 --> 01:34.610 types of LM and what they're capable of, whether we're talking about open source versions, the closed 01:34.610 --> 01:40.220 source paid versions, ones that are multi-modal, that can generate images or audio, the different 01:40.220 --> 01:45.920 architectures of LMS, and importantly, how you pick which LM you should be working with in the first 01:45.920 --> 01:46.610 place. 01:46.610 --> 01:53.270 We'll be looking at all of the tools of the trade, things like the ubiquitous hugging face, the super 01:53.270 --> 01:58.490 impressive glue code in Lange chain, the fabulous gradio that you will see. 01:58.520 --> 02:01.130 I'm a big fan of weights and biases. 02:01.130 --> 02:05.270 Super helpful and then modal for deploying it to production. 02:05.270 --> 02:10.790 And we'll be looking at techniques different ways that you can apply this. 02:10.880 --> 02:18.590 The field of AI to solve business problems from using API's Rag which is such a hot topic, fine tuning 02:18.590 --> 02:23.360 and then at the end a full Agentic AI solution. 02:24.830 --> 02:30.170 The idea of this course is that I've planned it so that it will apply almost no matter what your level 02:30.170 --> 02:31.400 of experience. 02:31.640 --> 02:36.350 You may find initially that some of the first few weeks are too simplistic for you, or the first few 02:36.350 --> 02:37.130 days at least. 02:37.130 --> 02:42.980 And there I would say hang in there, use it as a way to just sort of reinforce some of the of the foundational 02:42.980 --> 02:47.570 information that we'll talk a bit more detail about things like tokens than you've done before, perhaps. 02:47.570 --> 02:52.400 So there'll be stuff to pick up, but you can go through it quickly and then make the projects your 02:52.400 --> 02:52.730 own. 02:52.730 --> 02:59.600 So use it as a way to build deeper versions of what we do and then prepare for harder, fun projects 02:59.600 --> 03:00.980 coming up later. 03:01.190 --> 03:05.510 If it feels too challenging, then please, please don't worry. 03:05.540 --> 03:07.910 Take your time with the practicals. 03:07.940 --> 03:09.860 Take your time with the exercises. 03:09.860 --> 03:11.210 Work your way through them. 03:11.210 --> 03:15.650 There are some extra guides that I'll talk about in week one that would help give you a sort of firmer 03:15.650 --> 03:16.790 footing if you need it. 03:16.790 --> 03:19.550 And please, please, please ask for help. 03:19.550 --> 03:21.620 I am here, I respond quickly. 03:21.620 --> 03:27.290 You can always reach out to me, either as I say on the platform or through email or through LinkedIn. 03:27.320 --> 03:29.180 Details are in the GitHub repo. 03:29.180 --> 03:30.290 Reach out to me. 03:30.320 --> 03:31.130 Get help. 03:31.130 --> 03:32.600 That is what I'm here for. 03:32.900 --> 03:35.810 And then if it feels just right, then excellent. 03:35.810 --> 03:36.770 Keep going. 03:37.580 --> 03:43.880 So the prerequisite is beginner to intermediate level Python. 03:43.880 --> 03:49.370 And if you have intermediate level Python you're going to find it easiest and you'll get the most out 03:49.370 --> 03:50.060 of it. 03:50.180 --> 03:55.280 And if you look for example at this line of code right here, which is just a random line from within 03:55.280 --> 03:55.910 a function. 03:55.910 --> 04:01.280 If you basically know what that's probably doing, then you're in great shape if you know exactly what 04:01.280 --> 04:07.250 it's doing and if you know in fact why, it's not perhaps the most optimal way of doing it, then you're 04:07.250 --> 04:12.260 more than more than, well set that you're advanced, and that's great if you don't know what this does 04:12.290 --> 04:19.910 and you're not familiar with a world with a word like yield or set or the dot get, then there is a 04:19.910 --> 04:27.890 special notebook, a special Jupyter Lab in week one for you, which is a guide to to Python at this 04:27.890 --> 04:28.490 level. 04:28.490 --> 04:33.890 And as you go through that notebook, I will take you through each of the stepping stones until we get 04:33.890 --> 04:36.620 to a point where a line like this should make sense. 04:36.620 --> 04:40.550 And of course, you can also use ChatGPT and Claude. 04:40.580 --> 04:45.320 The the the genies are really good at explaining code. 04:45.320 --> 04:49.310 And indeed, if you put something like this in there, they would tell you exactly what it does and 04:49.310 --> 04:50.780 why and step you through it too. 04:50.780 --> 04:54.200 And they're probably just as good as, as my, my notebook. 04:54.200 --> 04:57.050 So either way, that should give you what you need to do. 04:57.050 --> 05:01.640 And at any point, if you don't understand some code, you can always use ChatGPT. 05:03.230 --> 05:08.630 So to get the most out of this course, there are a few things that I would ask you. 05:08.660 --> 05:12.410 First of all, follow along as I do my coding. 05:12.410 --> 05:16.640 So when I'm when I'm going through in the labs and I'm executing cells, then either at the same time 05:16.670 --> 05:18.890 or afterwards go through and do it yourself. 05:18.890 --> 05:25.100 And if you hit snafus, which you might do for various reasons, then have a crack at trying to to sort 05:25.130 --> 05:25.640 out why. 05:25.670 --> 05:26.540 Do some debugging. 05:26.540 --> 05:33.380 That's a great way to learn and complete the exercises, and then put your code examples up on GitHub. 05:33.380 --> 05:34.670 It's actually a great way as well. 05:34.670 --> 05:39.770 If you're new to this space, and you're trying to build up something of a kind of resume to show that 05:39.770 --> 05:45.290 you've built some of this experience, the best kind of resume you can have is a GitHub repo, because 05:45.290 --> 05:48.380 people will look at it and will see the sorts of things you've worked on. 05:48.380 --> 05:51.170 And of course, you don't want to put exactly the projects we do. 05:51.200 --> 05:52.910 You want to make them your own. 05:52.910 --> 05:57.800 You want to figure out, okay, how can I apply this to my business area or to a personal project that 05:57.800 --> 06:01.160 I'm working on to make it something that's similar, slightly different? 06:01.190 --> 06:03.950 Take on it for new business value. 06:04.010 --> 06:10.760 That is a great way to get the most out of this course, and then look to share your code. 06:10.760 --> 06:13.130 If you're happy with it and you and you're okay with that. 06:13.130 --> 06:18.140 I've got instructions about how you can submit a pull request, which means that I can see your code. 06:18.170 --> 06:23.660 I can give you feedback on it if you'd like, and I can also then republish it so that other students 06:23.660 --> 06:27.590 taking the course will see your examples and we can all share in it together. 06:27.590 --> 06:29.540 And of course stick at it. 06:29.570 --> 06:30.950 Hang on in there. 06:30.980 --> 06:34.550 This course gets better and better and better, I assure you. 06:34.550 --> 06:39.440 And I you know, there's there's going to be so many projects, so much commercial application. 06:39.440 --> 06:43.550 And I definitely encourage you to stay the course. 06:43.580 --> 06:48.410 And the thing I didn't put down here one more time is that getting the most out of the course. 06:48.410 --> 06:52.220 Also, please reach out to me if I can help at any point.