Today, data science is still among the highest in-demand careers and climbs further up the ranks each year. That being said, mathematics is a blockade for freshers and new career pursuers. So the question of, can I become data scientist without maths has become the first question among young pursuers of data science.
Moreover, the need for data scientists is a direct response of society to our growth. These professionals boast a constant value in the market due to the ratio of supply and demand. Relatively speaking, the need for data scientists shouldn’t go down anytime soon.
Indeed, as one of the careers that can set you for life, aspiring to become one shouldn’t be a surprise. However, there are a few caveats to becoming a full-fledged data scientist. Proper education aside, there are quite a few conditions that remain pique the curiosity of many. Can you become a data scientist without mastering mathematics? And can you be successful without it altogether? Let’s take a deep dive into answering those questions today.
Data Science: The Multi-Field Network
Evolution is the sole proof of how much growth humanity is capable of. More importantly, as we evolve further as a species, our capabilities expand with our growth. Data is one of the constants that will always stay in a loop of change regardless of the era. For this reason, data science is undoubtedly one of our strengths moving forward.
Data science is a network of various disciplines interwoven to create a network of programming, data mining, and statistical knowledge. Moreover, there can even be different specializations for each data scientist. These individuals communicate with data, capture and analyze volumes of information, and finally maintain its integrity.
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Value and Demand: Is it Still Worth Studying in 2021?
The value of this profession is only surpassed by Front End Engineers and Java Developers, both of which share similar fields with data scientists. Looking at how the current state of the world is reacting to the pandemic gives us an idea of how data science is crucial to overall improvement.
Google, Amazon, and Facebook are still among the largest companies in the world today. Moreover, they have grown exponentially in their respective markets, primarily due to the influence of data scientists. These companies use data science to create profit in the form of algorithms that cater to customer satisfaction.
Primarily, data science remains one of the most sought-after professions due to its versatility in creating opportunities for companies. Massive organizations tend to adapt quickly to profitable trends. Therefore, data science techniques, tools, and applications are essential to staying ahead of the competition.
Interestingly, data science is still considered a new field in 2021. It is because of how difficult it was to study with the past’s limited hardware and software resources. However, with the latest machinery and technology on the way, data science marches forward with innovation and growth.
Do You Need Math to Be a Data Scientist?
Most people have a natural ability to learn anything they want with determination and focus. However, some individuals progress slower than others and lose valuable time in the process. Unsurprisingly, learning mathematics is one of the most time-consuming lessons of any education. This is why the question, “Can I become a data scientist without math?” comes into mind.
The answer is yes and no. Indeed, becoming adequately capable in data science can be learned outside of traditional learning with just the fundamentals. On several occasions, an aspiring data scientist often gets misinformed regarding the difficulty of mastering the discipline. As a result, various misconceptions arise and overwhelm those who wish to become data scientists.
If you’re wondering, “Do you need maths for data science?” then the answer is also a definite yes. However, your idea of mathematical ability might be slightly different from what is needed in the field. You don’t need to be an arithmetic genius, but mastery of specific techniques is a must.
Practical Learning: Mastery of Important Mathematical Concepts
As mentioned earlier, you don’t necessarily need the arithmetic prowess of a maths professor to become a data scientist. However, this is because you’re ready to put in the time and effort to learn key concepts. Does data science require math expertise in every area? Definitely not.
Some of the most apparent concepts are Algebra, Statistics, and Calculus. If you already have a background in some of these areas, you probably know how data scientists implement them. More importantly, the best approach to becoming a data scientist is to focus on the lessons critical to your research.
Which Skills Should You Consider Learning?
In Data Science, a plethora of skills exist to help you remain a step ahead of work. However, a few soft skills can complement an aspiring data scientist who has little to no experience in mathematical techniques.
Here are some recommendations to consider:
- Data Analysis – The ability to accurately display data in graphs, charts, and visual representations. Data scientists also need to be able to scan and evaluate patterns in data. Finally, you can also brush up on efficient collecting, cleaning, and handling values.
- Programming – Data science exists on a plane created for and by programming languages. These are namely Python, R, and SQL. Indeed, this recommendation takes the top spot for soft skills each data scientist should have in their repertoire.
- Machine Learning – Smart technology is definite proof of humankind’s creativity. Therefore, data scientists at the forefront of innovation should boast mastery of various libraries in this field. Some of the notable ones include XGBoost, PyTorch, and LightGBM.
Is Maths required for Data Science? Well, if you already possess some of these skills, then chances are you might already have what it takes to master both. Most people find it daunting to think about handling data with complicated math formulas. However, nothing worth doing comes easy. Therefore, focus on the things you need as you study and work your way towards becoming a full-fledged data scientist in the future.
Verdict: Do You Need Math to be a Data Scientist?
Math shouldn’t deter you from learning data science. More importantly, every aspiring data scientist in this field should consider the possibility of developing a love for mathematics as you grow deeper into the field intellectually. Indeed, there are a few occasions where those who didn’t like the subject produced a passion for it along the way. Finding the median between practicality and the motivation to keep pushing forward is what separates successful data scientists from the rest.
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