If you are here, it is probably because you are on the cusp of choosing a career path and data science is calling to you with its promises of being the career to have in the 21st century. Or you probably just heard about it somewhere and are curious to know more about it.
Nonetheless, read on to find the answers to the following questions: Is data science a good career? Is it easy to pursue? Would it be viable to go down a different path instead?
A field associated with computer science, data science is focused on coming up with algorithms and methods to extract information and trends from raw data to make informed decisions.
And with the definition out of the way, let us get into the stuff that you probably care more about.
Is Data Science Hard?
While the difficulty level of anything is subjective and varies according to what a person might find grueling, the consensus is that data science is not extremely hard. Sure there are skills you will have to arm yourself with, but at the of the day, they are not impossible to get the hang of.
Initially, you will be required to have a grip over a variety of software, tools, and programming languages. This will sound overwhelming to someone who is just starting out, but it is important to note that the skills from learning a programming language are transferrable to other languages. For example, if you are adept at Java, Python will come readily to you.
Therefore, pushing yourself to get started with learning data science is a more daunting bit than the career itself.
However, before you become too relaxed, it is important to keep in mind that it is not enough to be proficient at mathematics—statistics to be particular—or coding, but you must rewire your entire brain to think analytically.
A good data scientist will have to know the appropriate models to employ on the different sets of data to be able to derive accurate conclusions. Hence, you should not go into data science thinking statistical skills will be enough.
Picking incorrect structures for data representation and analysis could lead to problems down the road.
In addition to that, you must make sure that you are constantly practicing the things you have studied. You must practically implement whatever you learn.
Despite all this, data science is not particularly hard.
As mentioned above, all the various skills that go into being a good data scientist are related to each other. Building one will help you build the others. Therefore, unlike some other disciplines where you must internalize several unrelated pieces of knowledge, data science is highly interconnected and specialized.
The skills needed to pursue data science professionally can be learned with some effort and persistence. Nowadays, several universities offer data science majors and minors.
The consensus suggests data science is equally difficult as other STEM majors including computer science, economics, and statistics.
Furthermore, relevant experience can be earned by freelancing as well as participating in hackathons and other competitions. This will even allow you to practice professionally without having gone to a dedicated degree program.
It takes around under a year for a person to be sufficiently proficient to begin practicing as a data scientist. When compared to other degrees, this is a generous timeline and can be credited to its relative ease.
All in all, data science relies on you being smart with your learned concepts rather than rote learning for four years. If you can do that, you can be a good data scientist easily.
Is Data Science Harder Than Computer Science?
Computer science is harder than data science because it encompasses a larger number of topics, has more intense programming, and requires advanced technical skills. These factors combined make computer science a challenging and difficult field.
You might wonder, how could data science not be harder if it is more specialized and requires your thinking to be a certain way?
It is true, that in addition to programming, in data science you will be asked to use that to run algorithms for data manipulation, representation, and analysis. If you are formally pursuing a degree in it, you will take laborious but mentally stimulating courses like Regression or Financial Modelling—depending on your line of work.
Conversely, computer science, while does not itself get into such nitty gritty details, spans over a diverse range of fields such as software engineering, hardware, computer architecture, and computation among other things.
A computer science degree does have a few courses covering statistics but not to the extent of data science. Similarly, the most advanced math course in computer science is linear algebra. But the programming and technical skills you will learn with computer science will still be superior as compared to data science.
Furthermore, you can pursue a master’s degree in data science after doing a bachelor’s in the former whereas the reverse is not a very popular choice.
Nonetheless, it also depends on you at the end of the day what is harder for you. What side your brain is disposed to ultimately decides what you will find easier.
Is Data Science Better Than Computer Science?
Data science is not better than computer science. Both data science and computer science are excellent fields offering high wages, superb benefits, and research opportunities. You should choose the subject you are more interested in.
It is quite subjective whether data science or computer science is better. Both have their own merits and demerits, almost equally balanced. Therefore, it is your interest that will dictate if you find data science to be the more distinguished field. But if you are undecided, it is better to go ahead with computer science.
If you want to study distinct and varying topics, computer science is the way to go. Say that you are curious about various fields, then data science will severely limit your areas of focus. If you want to know how the fundamentals of computers in addition to programming and network engineering, you will find that data science does not expose you to such fields.
Following that line of thought, if you are undecided about what you want to specialize in, a highly narrow field such as data science is not recommended. You will not be able to explore and decide your niche.
Computer science will allow you more flexibility in terms of topics you study and the careers you pursue.
On the flip side, however, if you decide that specialization and playing around with data is exactly what you want, then data science is definitely the field for you. If a focus on storytelling through data, exploring answers to strategic questions and employing logic sound interesting then you should not hesitate in selecting data science.
Furthermore, you can enhance your understanding of machine learning and representation models. And if that is what you find yourself drawn to, data science is ultimately for you.
Is Data Science a Good Career?
The answer to this is trickier than most. Famous for its good pay, it is a field that is getting saturated, at the entry-level at least. Therefore, depending on your skills and experience, data science could be a good career for you but not everyone.
A very attractive prospect about this job is its salary. Even as a beginner, you will be offered good pay compared to other fields. Therefore, the draw is decidedly there. And from here your salary will only go higher as you progress as a professional.
You should not face significant obstacles in finding work in a hot field such as data science, as companies rush to make data-driven decisions.
If you dig deeper and talk to data scientists and professionals in data science, you will discover that the field is seeing an influx of beginner-level data scientists. Drawn to its benefits and the fanfare, many people are making a switch to this career which means sooner or later there will be more data scientists than job listings.
However, if you have an experience that puts you in a comparatively proficient position, it will provide you with ample opportunities.
Conclusion
Revolving around data modeling systems and statistical number crunching, only people who are captivated by such work should be encouraged to actively pursue it. Otherwise, you might find it too dry for your liking, too technical, or even that the demand for you in the market is too low by the time you are ready to practice professionally.
And if you are still unsure after reading about what being a data scientist entails, perhaps it might not be your calling. A more multifaceted area such as computer science would be better for you.
However, if you are up for a challenge and would constantly want to push yourself, you would be a great fit for data science.
