 Have you ever felt really overwhelmed by the probability of data science, learning where to start or how to stick to your learning? I used to dabble aimlessly when trying to learn technical topics, but I now have a much more systematic approach which has really transformed my understanding. In this video, I want to share my techniques, advice that helps help me in my learning journey and general tips for staying consistent. Let's get into it. Naturally, the first step in trying to learn something is to decide exactly what you're going to learn about. Now, most people probably have some general idea of what they want to learn, but simply saying I want to learn data science is probably quite insufficient. Data science is an area that encapsulates so many different subjects, such as maths, statistics and coding, to stay the obvious, and these areas can be broken down even further. While it may sound boring or mundane, I find having a really detailed roadmap or syllabus is a real game changer for learning anything. Chances are there's someone on the internet who has the knowledge you want and they've written some sort of blog, made a video or any bit of content explaining the things you need to know to get to where they are. So you can pretty much get a description of everything you need to know in 10 minutes or less, which is truly amazing. You can also Google things like data science roadmap or software engineering roadmap and just pick all the top hits they like the most. And another more niche way is that when I was trying to learn statistics, I went to my old university's website and looked down to the mathematics and statistics bachelor's degree. I then went over the first and second-year modules and basically the content in those modules was exactly the things I went about learning when I was trying to develop my knowledge in statistics. This option is free to anyone, just go to any university website, look for the courses or modules that you're interested in learning and look at exactly what they teach and that's basically your syllabus for the topics you should learn. Getting started with your learning journey is a lot simpler than you think and it only takes around an hour max to get a really good roadmap or syllabus for you to study. If it takes any longer than that, then you're doing something wrong. After figuring out exactly what I need to learn and the different areas that I need to understand, I then go about finding some material to learn these topics. I vary the resources I use, sometimes it will be an online course, a video or even plain old Wikipedia. I often have one core resource and then I supplement with others. For example, when I was learning deep learning, I used their hands-on cycle learn with machine learning textbook as my main core text but I would often supplement with videos and blog posts to help understand the concepts in a lot more detail. Mixing learning resources is something that really helps me because I think having different diagrams, videos, texts kind of explain things in different perspectives which allow me to piece more of the puzzle together and get an overarching view of the whole topic. In terms of finding the right course, I don't worry too much about this and normally just pick something that's highly rated and popular. I don't try to find the best one because chances are that doesn't really exist because it really depends on you as a person and how you learn. After I have got my detailed roadmap and I found the material I'm going to use to study, I then try to block out time on my calendar to dedicate to studying this topic. As I am a hybrid worker, I basically use my commute time as my study time, so every morning 8-9 and every evening 5-30-6-30 I would dedicate to studying this technical topic that I'm trying to learn. I think everyone can find pockets in their day to dedicate to studying, even if it's just half an hour, but I do appreciate that this may be easier for some people than others. In one of my previous newsletters, I wrote an article after reading a book Stolen Focus, which was all about how our attention is being stolen from us and has been degrading over the past few decades. The book showed me that there's a real attention problem out there and being able to focus for a long period of time is a real superpower With this in mind, in my study sessions, I turn off all notifications and all distractions so I can focus 100% and give my undivided attention to the study I'm currently doing. It's really amazing how much you can achieve in such a short time, like an hour, if you're just zoned in on something 100%. And finally, when I'm studying, I'm not simply just trying to tick things off a list or measure the amount of time I'm putting in, I'm really trying to gain a deep intuition and understanding about the topic I'm learning. It's about delving deep into the subject matter and really comprehending it. And this process can be quick or lengthy, depending on how much knowledge you have from before and just how quickly it takes you to fully grasp it. For example, it took me ages to really understand exactly what neural networks are doing and the main intuition and engine behind how they work. Studying is merely the first step in mastering a subject. To gain that real deep understanding, you need to have some practical applications and hands-on experience. This is particularly true for applied areas like coding. You can never be a really good coder by simply studying the theory, you have to go out and build things on your own from scratch. One of my fundamental principles that I use is that I learn just enough and then I immediately go and start doing projects and building things from the knowledge I just acquired. For example, if you're trying to become a data scientist, learn just enough statistics, machine learning, Python, and then go out and do a project because that's how you're really going to learn and get a real world experience. I promise you that most successful practitioners in any field preach this approach. And whatever you do, don't get stuck in tutorial hell. Doing course after course after course will have diminishing returns and eventually you'll just plateau and you'll be learning nothing new extra. Another great way to really build intuition behind a subject is through teaching and this is something known as the Feynman technique. By teaching you are both slidifying your understanding and also exposing the areas you lack knowledge of and therefore you can iterate through this process refining your knowledge each time. I do this approach all the time through creating videos and making blogs. I can't tell you the amount of times where I've sat down to write a blog and I've realized oh I don't know this part or I don't know this part and I'm slowly building that picture up and this process of teaching or making content about the things you learn is really powerful because like I said it will expose your knowledge and it'll show you where you're lacking understanding and then you go refine on this and that's how you develop that kind of expert and real mastery of a certain subject. If you're up to it then I really recommend that you make some sort of content on the things you are learning. That can be anything from a Twitter thread to a YouTube video but I promise you that is a very useful technique and it will amplify your learning tenfold. If you don't fancy writing blog posts or making videos you can always present your knowledge and understanding to a family member or a friend and even if you don't fancy that you can always take the rubber ducking approach and present your knowledge to some sort of inanimate object. During this learning process there'll be days where you don't fancy booting up your laptop or whipping out your notebook for another study session. When this does happen I recommend the following tips to help you stay consistent. The first one is that when I don't fancy studying I tell myself just do five minutes and often just doing that first five minutes will get me in the mood and I will often study for a way longer period of time than I initially intended to. The second one is I make my study blogs as scheduled in my calendar as non-negotiable. Again this can be quite difficult because it requires a bit of a mindset shift but once you get into that habit and routine it's actually quite easy and you make sure you don't miss them. The third technique is that I have a strong why behind why I'm learning something and this helps me keep me accountable. The fourth one is that I frequently log my study sessions. This allows me to build a streak and get momentum and when you have momentum it's quite hard to stop. And finally the fifth way is that I gamify my learning somehow and I normally do this through celebrating small wins and having little checkpoints. This gives me that sort of dopamine hit which allows me to keep on going and build my confidence. All in all anything that can make the process more enjoyable and learning more fun will allow you to stay consistent. So let's quickly summarize the key steps I take when trying to learn a technical subject. The first step is that I get a detailed syllabus of roadmap which gives me a direction in my learning. The second method is that I try to find some material. Again I don't worry too much about this. I just find something that's popular or highly rated and I just go with that. I then fully commit to learning this topic by booking blocks in my calendar and giving it my undivided attention during that time. I try to learn just enough then immediately go work on projects and get hands-on experience. Finally I use things like the Feynman technique to really submit my understanding through teaching the topic. If you enjoyed this video and want to hear more from me then I write a weekly newsletter called Dish in the Data. It's a newsletter that I send every Monday morning and it's all about my thoughts and insights as a data scientist. If that sounds interesting then it's linked in the description below for you to check out. 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