Data science is a career that is becoming highly sought after and popular not only among students but also employers, especially with the advancement of technology.
If you are a student who will be starting your tertiary studies soon, during your research, there is a high chance you will come across the term ‘data science’. It is after all named one of the sexiest jobs in the 21st century by Harvard Business Review.
Before we go any further, it is pertinent for you to understand what is data science. In basic terms, data science involves analyzing data to uncover valuable insights and information for practical use.
Many people might not realise the importance of data and how it affects our lives. More often than not, people think that data is something that is more of use to big businesses or the government and organisations but did you know that they actually are relevant and affect each of our lives? Data is something that plays a part and connects us all whether we like it or not.
Are you aware that data is what helps us make more informed and better decisions and this same data is what helps organisations and businesses come up with strategies and plans to improve their business? This is the core reason why data science is very much in demand.
When you learn data science, you will also learn many other multidisciplinary fields. You will learn computer science, mathematics, science, artificial engineering, statistics and many more. You can learn statistics from a private tutor from Superprof if you are interested!
One thing is for sure, data science is not only vast but also interesting and requires a lot of dedication to learn and master. If this seems like something that interests you, read on!
Getting to Know Big Data and Big Data Analytics
One of the most basic things you should know and understand when it comes to data science is big data and big data analytics.
Big data is simply data that is too big for a normal person or even a normal computer or processing software. In order to explain this better, let us look at the history of big data and how this term was coined.
Did you know that the phrase "big data" was first introduced by John R. Mashey back in the 1990s? It might come as a surprise to some but data has been used since early civilisation. It was used not only to help people in their decision-making, similar to how it is used even today but also to gain an advantage in the military. Some of the earliest reported and documented cases of big data come all the way from the Roman Empire. Big data is used to identify algorithms and has been used for centuries. It is at the beginning of the 21st century the volume of data generated is bigger and more than what humans are able to comprehend. This is due to the rapid growth of technology that has boomed in the 21st century.
With these, came data analytics. Data analytics is closely related to data science whereby it is the act of processing data to determine and identify useful information that can help with not only better decision-making but also making conclusions. The importance of data analytics cannot be ignored as it is a core and valuable part when it comes to decision-making within an organisation. Generally, there are four key types of data analytics: descriptive, predictive, prescriptive, and diagnostic. All these four play an integral part in the overall picture when it comes to data analytics. If you would like to know more about the core concepts every data scientist should master, click here.
The Role of a Data Scientist
Now that you have a brief idea about data analytics and big data, it will be easier for you to understand what a data scientist does.
In general data scientists are people who convert data into insights for an organisation or company. They are people who are able to compile, arrange and interpret data and find insightful patterns to help decision-making. Their skills are like no other. Where normal people would be random, data scientists are people who are able to identify patterns and interpret them.
This alone shows that data scientists are people with a specific skill set which makes them highly desirable and employable. Their skills are what is required, needed and in demand. It not only helps people make decisions but they are highly sought after by stakeholders and decision-makers within an organisation.
Did you know that there are many different types of data scientists? Data scientists in different industries do different things. For example, the types of data scientists include but are not limited to the fields of finance, health, retail, academia, information technology and many more. They are people who perform data analysis, identify issues, propose solutions and help organisations. This job also requires you to not only have great interpreting skills but also communication skills as you will be working closely with other IT teams and professionals, different departments within the organisation as well as stakeholders.
Machine Learning and Deep Learning Explained
Artificial intelligence is something that has boomed in the past couple of years but did you know that the first artificial intelligence started all the way in the 1950s? Although artificial intelligence existed for a long time, the term was only coined recently in the 1990s.
Artificial intelligence has revolutionised the world and things that seem as difficult or impossible are not only possible but readily available to each and every one of us. One such example of this is machine learning-based financial fraud detection.
Machine learning is a part of data science that is linked very closely to artificial intelligence. So what is it exactly? Machine learning is generally referred to as ML and it is a branch of data science that looks at using data to enable artificial intelligence to learn and improve similarly to how we humans learn new things. Machine learning models are not only able to impressively learn patterns and algorithms but also predict values based on historical data and categorise events and cluster data points.
One of the examples we provided earlier is machine learning financial fraud detection. In this day and age where financial fraud is rampant, this new discovery is pivotal to the fight against fraud. It has enriched and helped organisations all over the world to identify and prevent fraud.
Another important term if you are someone considering data science is deep learning. Deep learning is a subset of machine learning. It deals with artificial neural networks which are impressively inspired by the structure of the human brains. As a result, deep learning achieves greater accuracy. Although you might not have used this, all of us have heard of ChatGPT.
Both, machine learning and deep learning are linked to artificial intelligence but they are a bit different in the sense that deep learning outperforms machine learning especially when it comes to complex data and recognition tasks.
Your Path to Becoming a Data Scientist
With the advancement of technology, becoming a data scientist is something you should really consider. The global demand for data scientists is rising, not just in Singapore.
It comes as no surprise that data scientists earn good money due to their skillset so if you are someone who is considering getting into this line of work, you are at the right place.
One of the first steps you should take in order to get into the world of data science is to obtain a degree. You can get into this line of work with a data science degree or even a degree in mathematics, computer science or even statistics. Some of the universities you can consider in order to obtain these are NUS which is the National University of Singapore, or even SMU which is the Singapore Management University among others. Getting the relevant degree will provide you with the knowledge necessary as well as the skills that will help you thrive as you step into the world of employment.
As you know technology rapidly grows and changes and now with the introduction of artificial intelligence, the growth we see in technology is rapid. One of the best things you can do is to keep yourself relevant by obtaining certificates such as SQL databases and Python. These are some examples that can help you grow and ensure your knowledge remains relevant.
Check out How to Tackle Your Statistics Exam.
If you are someone who is interested in learning data science or statistics, starting might seem like a daunting step. We here at Superprof believe in helping students grow and learn. If you are located in Singapore, we have tutors that are available in Superprof that can help you learn and understand data science.
Our tutors are not only highly skilled and qualified but they are also passionate to impart and enrich the lives of their students. We have a wide range of tutors that come from a diverse background so we are sure you will be able to find a tutor that suits not only your requirements in their skills and qualifications but also someone that will fit your budget.
Most of our tutors also provide their first class for free so you can rest assured that you can try out their class before committing to taking their course. This gives both the tutor as well as the student a chance to see if they are a good fit.
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