Whether you are interested in becoming a data scientist or just curious about data science, then you might have already asked the question, “Is data science hard?” The answer, however, is not a clear yes or solid no but more of it depends. To find out if data science is hard, it’s important to take a closer look at the subject.
What is Data Science?
Before you ask, is data science hard, you need to know first what is data science anyway? Data science is the study of extracting meaningful insight from data by using mathematics, statistics, programming skills, domain expertise, artificial intelligence, and more.
Data science deals with everything about data from the extraction of said data, processing, and wrangling. The end result is insights from said data that can be used to improve or create something. To give you a better idea, below are some examples of the applications of data science.
Applications of Data Science
So, what is data science used for exactly? There are many ways that data science has helped improve or continue to improve various fields. Here are some uses of data science in different fields:
E-Commerce
Do you ever wonder how or why when you are on Facebook and Instagram, it seems to show advertisements of things that you want or need? It’s because companies have now been using data science to find out everything they need about their customers.
With data science, companies will find out who their target market is, what their target market wants, when they are online or active, and many more.
Social Media
On your social media accounts, you might also be wondering how people you haven’t heard from in a while suddenly adds you. Or maybe, you are surprised to find them in the “People You May Know” category. Data science is used for this, linking people who belong in the same city, area, school, or group.
Sports
It might be surprising for some, but data science is also used in sports. Teams are able to identify which players to send out to the field or bench with data science. It’s even used to figure out how basketball players should shoot their shot to score a 2 or a 3.
Health & Medicine
A perfect example of the application of data science is in the world of health and medicine. Take the 2020 pandemic, data scientists are able to trace who are the infected people with data science. It also helps in how to contain people who are infected, the effectiveness of masks and vaccines, and many more.
Requirements for Data Science
Now that you know some of the applications of data science you might be more interested now in learning the subject. So, what do you need to become a data scientist, or even just to start getting a deeper understanding of data science?
Equipment
You don’t necessarily need the best laptop for data scientists right away. Although you might want to consider investing in one from the get-go if you plan on doing data science in a professional capacity. But definitely, you will need a computer that can handle data mining, coding, data munging and visualization, and more.
Knowledge
To be a data scientist is to be a jack of all trades. You can’t rely on just being good in math or statistics alone. You also need a background in coding, how to understand databases, and more. Technology and science are ever-changing, so you will always need to be up-to-date on a lot of things. Being a data scientist is a constant state of learning.
Experience
Data science is not something you can learn from books or schooling alone. You will need the experience to become a data scientist. Think of it like driving or riding a bike, you can watch other people do it, you can load up on Youtube videos, or read about it in books. But you will never really learn until you hop on a bike or get in a car yourself and start pedaling or step on the gas.
Although not impossible, you won’t be able to get a job right away as a data scientist. If you want to gain experience, you can get help from a community or group of data science beginners or enthusiasts. You might also consider joining a boot camp or applying for an internship.
Conclusion
After getting a bit of background information on data science, its applications, and requirements, you might be able to answer the question, “Is data science hard?” on your own. Again, learning data science will depend greatly on you. If you already have a background in coding and statistics, then it might be a little easier for you to learn data science as opposed to someone who has zero knowledge on any of the studies empirical to data science.
