The 5 Stages of Learning Data Science

In this video I talk about how to progress through the 5 stages of learning data science. I will talk about my data science journey and how I "leveled up" from one stage to the next. Subscribe: https://www.youtube.com/c/kenjee1?sub_confirmation=1 Stage 1: Unconscious Incompetence (Novice Data Scientist) - In this stage the field may seem relatively easy. After watching some youtube videos and learning some python or r basics, you will learn how large the field of data science is. Free data science course recommendations: https://www.youtube.com/watch?v=Ip50cXvpWY4 Stage 2: Conscious Incompetence (Overwhelmed) - In this stage you will begin to understand the different elements of programming and statistics. Most people get stuck here because they don't know where to start. To get to the next stage, you should narrow the boundaries and start with a small data science project. Learn the necessary skills to complete that task, then move on to another small one. You should also go on kaggle and review code of other data scientists. Keep a log of all the terms, algorithms, and packages that you don't know. Stage 3: Conscious Competence (Slightly Dangerous) - Here you will have had a few projects under your belt. You will now be able to reuse your python or r code. This is where you truly learn data science. You should do as many projects as you can and learn to code data science algorithms from scratch. Stage 4: Unconscious Competence (Art Form) - At this stage, you know how to solve problems as they come along. You don't have to refer to your data science scripts, and you can start focusing on producing results. Here, you start to focus on optimizing your models. Stage 5: Mastery (Contribution) - While I don't believe that anyone has mastered data science, I believe that you reach this data science learning stage by contributing to the field in a meaningful way. There are few people that reach this stage, and most of them are likely living in academia. #DataSc