Big data is big business. It is estimated that by the year 2025, approximately 463 exabytes of data will be generated around the world every single day. It is almost impossible to put a number that large into context, but to make it more understandable, every day around 306.4 billion emails are sent and received, 500 million tweets are posted, and 5 billion videos are watched on YouTube. The global online population is continually growing, and the amount of digital data generated is growing right alongside it. Yet all of this data is virtually useless unless you know how to analyze it. That is where data science comes in. In this article, we will discuss what the subject involves in more detail, and why it is such a fantastic field to get qualified in.
Also Read: How Data Science is Used in Manufacturing
What is Data Science?
Data science is concerned with the efficient management and analysis of big data. It involves using a combination of computer programming, mathematics, and statistics to extract valuable insights from the huge volumes of data that are constantly being generated. By finding patterns, data science can help organizations and other stakeholders to make more informed decisions in almost every industry. This can then enable people to solve a wide range of problems and develop innovative strategies to improve performance. It is a field that is relevant to sectors as diverse as healthcare, finance, retail, and entertainment, and one that is only becoming more crucial as technology develops further and data generation increase exponentially.
How Can I Move into the Field of Data Science?
If you are interested in getting a job in data science, you will most likely need a master’s degree in computer science, computer engineering, or another similar subject. Generally speaking, to enroll in one of these programs you will be required to have a bachelor’s degree in a relevant subject and proficiency in computer programming. Do not worry if you are unsure about the viability of returning to college, because these days you can study for an online data science master’s from the comfort of your own home. This means that you can learn alongside your day job or existing family commitments in a flexible manner, and sometimes even benefit from lower tuition fees. This is all while still getting the same high-quality education as a course that is based on campus and enjoying identical benefits after you graduate.
What are the Advantages of Studying Data Science?
There are many different advantages to be gained from studying data science. Firstly, graduates of the subject are in very high demand – the US Bureau of Labor Statistics estimates that jobs in the industry are set to grow at a much faster rate than average, which means you can expect good levels of employability and job security once you graduate. In addition, with a median annual salary of $126,830 in 2020, computer and information research scientists benefit from financial stability too. Plus, it is a field that is only becoming more relevant, so these advantages are very likely to increase.
What is great about data science is that these job opportunities extend across a wide variety of industries. Just about every large organization will need data science, whether they are involved in pharmaceuticals, telecommunications, or logistics. That gives you a great chance to carve out a career in a field that you are genuinely interested in. This includes opportunities to make a meaningful contribution to society, for example by working in healthcare or to work overseas if you have a desire to travel.
As well as these subject-specific benefits, there are also more general advantages that you get from completing a higher education course in any field. For example, you will develop a wide range of transferable skills such as communication, problem-solving, decision making, teamwork, organization, and time management – all of which will be useful to you no matter what career you go on to have. Finally, graduate school (whether you attend online or in-person) can be a fantastic opportunity to meet new people and broaden both your social and professional networks.
What is Studying for a Data Science Master’s Program Like?
Studying for a master’s in data science combines computational and statistical skills in a series of academic modules. Some of these will be mandatory, while for others you will have a choice between different optional courses. The exact titles will vary according to the college that you study with, but you can expect a selection something like the following:
- Statistical Data Science
- Statistical Computing
- Machine Learning
- Stochastic Methods
- Big Data Technologies
- Cloud Computing
- Information Retrieval and Data Mining
- Databases and Data Warehousing
- Natural Language Processing
- Data Modeling
- Risk and Decision Making for Data Science and AI
- Neural Networks and Deep Learning
These will involve a mixture of lectures, seminars, tutorials, and practical work, with assessments via examination and/or coursework. You will likely also have to undertake an independent research project towards the end of the course, for which you will write a dissertation. Students are given the freedom to choose their own topic for this, and as such many find it to be the most rewarding part of the program. On average, a master’s in data science takes a year to complete on a full-time basis or two years on a part-time basis.
How Do I Apply?
To apply for a master’s in data science, as well as meeting the entry requirements you will normally need to submit your resume and some letters of recommendation that can speak to your suitability for the program. You may also have to write a personal essay about why you want to study for the degree, and what your plans and career aspirations are. Some programs may additionally ask you to complete some short foundation courses in advance, to prepare you for what you will be studying in the degree modules. If that is the case, be sure to give yourself enough time to complete them. Do not forget to start looking into funding opportunities too, whether that is from your current employer, government financial aid, or scholarships.