As the career of Data Scientist has grown in popularity in recent years, aided by its designation as the “sexiest job of the twenty-first century,” Masters degree programmes in data science have sprung up. These courses can cost anywhere from $30,000 and $100,000, not considering the expense of living while you study.
Data science education is still primarily focused on identifying trends and patterns using statistics and messy data. Companies are increasingly hiring data scientists to bolster their analytics teams, which is why the discipline of data science is so lucrative.
However, the main question that arises is whether or not a person should go for a Master’s degree in data science.
Why You Should Not Take a Data Science Master’s Degree in 2022
There are a number of reasons as to why we believe that not taking a data science master’s degree in 2022 is a better option. A few of those reasons have been stated below for your better understanding:
- Master’s degrees are extremely costly. They also demand you to study for a set period of time, which can render them much more costly because you may not be able to work but also earn a livelihood while you learn. This is fine if you have the financial ability to afford for a degree and cover your rent and bills simultaneously time, but the fact is that so many individuals do not. This means you’ll either have to take on a lot of debt to pay for the course or you won’t be able to take it at all.
- Functioning as a data scientist involves more than just a basic understanding of statistics, mathematics, computing, and deep learning theory. In order to work successfully in a real-world data science team, you’ll need a variety of abilities that aren’t included in most Master’s degree programmes.
- These programs will not educate you how to use GitHub or why it is so vital for fostering collaboration with other data scientists along with data and software engineers in a company. They don’t cover agile, which is a methodology that many data science teams employ. They don’t educate you critical soft skills like interaction, inventiveness, and business acumen, which are crucial for a data science profession.
- Because data science is a combination of many distinct professions, it takes many years to perfect. Training through self-study and working in related disciplines will provide you with the breadth you require in all of these areas. A one- to two-year course will not adequately equip you for a position as a data scientist.
Why Should You Prefer Online Learning?
Anything you need to know about data science may be found online for free or at a very minimal cost. The additional advantage of doing so is that you may learn at your own schedule, which is ideal for your situation. So, if you have a full-time work or other obligations, you may arrange your studies around them and take as long as you need to learn the skills. You can also study in a style that is most convenient for you.
You can also try to obtain some actual experience in working with data or software in a real-world context while also doing self-study. Apprenticeship, freelancing, contests, participating to open-source projects, and finding work in strongly related fields like business intelligence or analytics could all help. This will expose you to the reality of working with data and technology, as well as provide you with verifiable experience that will help you find a position as a data scientist in the future.
What Is the Future of Business Intelligence in 2022?
Data is at the heart of both Data Science and Business Intelligence. While Data Science is the larger pool with more data, Business Intelligence can be looked of as a component of the larger picture. Further in this article, find out the future of business intelligence by checking out our article.
The latest BI trends, like any other technology, will tend to advance. From the early days of business intelligence, when it was limited to spreadsheets crammed with data, technology now allows for meaningful visualization and quick action. Today, business intelligence (BI) provides firms with new and innovative ways to boost efficiency, raise revenues, and better understand their consumers. As technology progresses at a breakneck pace, the future of business intelligence appears bright. BI tools and techniques will become more personalised and valued in 2022.
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