What I wish I knew when I learned Data Science

I started to learn Data Science in college but began to actively use it when working as Research Assistant. During my learning journey, I met lots of unnecessary mistakes that ended up in the learning block. In this article, I will share with you several mistakes that you can avoid so that you can experience a fruitful and smooth learning process.

When you are learning Data Science for the first time, there is a lot of ground to cover. You will encounter lots of difficulties. However, there are many little tips and tricks that can help you get started on the right path. The following are mistakes that have led me to those problems:

First, the common mistake that we make while learning Data Science is to try to cover everything in one big session. This will not work and will result in a trouble. It is better to start with something simple and build it up as you learn more.

The second mistake that we make is not to have a clear goal in mind. It is very important to know the purpose of learning Data Science before you start. If you do not know what you want, then it will be difficult for you to focus on the right things and get an effective result.

One of the most simple yet effective objectives is to create a sample project. You can do this by simply replicating other’s data science projects, and trying to modify them. It would help you to understand the process of data science workflow.

Moreover, you can also take a step further to combine data science project ideas to generate your own—remember the best idea sometimes is just a combination of great things (i.e. iPhone -> combination of phone, walkman, and camera).

Last but not least is to take a break for too long time. I believe, studying intensively over time is not really great as our brain has its optimal memory retention. We need to study in a smart way so that we can learn effectively.

However, I used to take a break too long after chunks of the learning portion, and sometimes forget to review my skills. Just like riding a bike, we need to constantly use it to be better at those skills.

Make sure that we target a reasonable break time until we get our hands dirty again with data science. One of the most effective methods is to set a Pomodoro timer to manage breaks within sessions. And, try to have a group study with a timely plan to manage breaks between sessions.

Best,

Ega Kurnia Yazid