Reasons to Learn Data Science in 2020

Data Science. Big Data. Machine Learning. Artificial Intelligence. These are all powerful sets of words. With genuine studies, numbers, and graphs, let’s together analyze why you should consider learning any or all of them.

Why learn Data Science or Machine Learning?

Data Science has been defined as ‘The Sexiest Job of the 21st Century’ by Harvard Business Review. Glassdoor, a world-known web site for job searching, ranked Data Science as the most effective job in America for 2019. Bloomberg relates to Data Scientists as the new Superheroes.

Data Scientists, Machine Learning Engineers, Data Engineers; all of these titles have two points in common: they are some of the most eye-catching occupations presently, and also they all suggest taking care of Information.

The Demand

The demand for this role has substantially increased in recent years, and it is most likely to continue to do so as shown in the following figure.

With such high demand for these kinds of players, people with a fair knowledge in any of these fields can find job opportunities across a wide variety of sectors.

Interested in the energy market? All the well-known firms in this sector are trying to find data-driven accounts to boost their decision making and process efficiency.

Enjoy consultancy? All the large firms (e.g. Mckinsey, Bain, BCG) are recruiting Data Scientists and Data Engineers to help their clients to use their data.

Want to work in a technology company? Google, Amazon.com, Uber, Facebook, are all seeking increasingly more Data Wizards.

The Wages

According to Glassdoor, the average income for a Data Scientist in the USA is $117,345/ year, way above the nationwide average, and like displayed in the following image, other related settings are not very far off.

The Marketplace

Apart from all of this, these jobs are in charge of implementing and building technologies that are reinventing industries, at the core of innovative emerging ones like Autonomous Automobiles or Advanced Image recognition tools, and these jobs will certainly be the key drivers in numerous forthcoming advancements in Industry and Academia.

The Marketplace for Artificial Intelligence is one of the marketplaces with the highest anticipated evolution, forecasted to hit $36 Billion by 2025 like shown in the following figure.

All of these breakthroughs are expected to be extremely advantageous for our societies, so having the chance to work in any one of these fields implies having the ability to make a lot of impact on the world and our quality of life. Many points can and will certainly be done with Artificial Intelligence, and those involved will be the torchbearers for our future.

To conclude, Data Science, Machine Learning, and other technologies are extremely promising areas that are interesting, fun, and have unlimited applications.

Regardless of there being a lot of experts, there is a shortage of certified professionals in these areas. If you turn out to be one more name in that list of professionals, you can also anticipate high-quality jobs and exciting remunerations.

All these areas have extremely high and increasing demand, and the compensations are excellent.

Okay, but what is happening currently?

Machine Learning is not a new field. Its beginning dates back to the previous century. Data Scientists have also existed for a while now under various names.

So why now? Why has there been such a claim for these kinds of skills in recent years? To answer this, there are two major reasons:

First, the incredible increase in the amount of data that is being created and consumed. Every day an increasing number of sensing units collect all sorts of data, and we, walking around with our mobile phones all day are massive sources of data also. The continuous development of the internet has also contributed a lot.

There is a great deal of data being produced than ever before. All this data is pretty worthless if it’s not evaluated or made the most of to provide value in companies or organizations. Its correct treatment permits better decision-making, process automation, understanding exploration, and a lot more.

As a result of this, the demand for profiles that can make good use of this data, and take advantage of it to its optimal potential has grown significantly in recent years.

Secondly, the rise in the available computing capacities has made it possible for us to develop systems that can successfully crunch all this data to get results in a reasonable amount of time.

Cloud computing platforms like AWS, Cloudera, Microsoft Azure and much more, which allow us to deploy and build smart solutions on extremely huge collections and machines from throughout the world, have significantly contributed to the practical enhancement of the feasibility of Artificial Intelligence Solutions.

Can I learn so much that I can make a career?

Yes, you can. There are countless sources– on and offline– where you can find out any of the building blocks that you may require to develop a career in one of these areas.

Don’t know how to program? Don’t fret, there are numerous platforms where you can learn, and to be truthful, you do not need to be a programming master to execute and build Machine Learning models.

Don’t know mathematics or algebra? That’s fine! With some basic algebra knowledge, you are fit enough to survive, nonetheless, a solid mathematical history can be helpful. Once more, if you wish to learn there are lots of outstanding platforms and resources available. Understanding of probability is also of great use and it is also not difficult to get a solid background solid enough to defend yourself.

Don’t know anything about Data Science or Machine Learning? Are babies born walking? Like everything else, learning about these fields is a process, which you can do by yourself by buying books, doing online classes and programs and become a self-taught Data Scientists, or you can enrol yourself to an actual bachelor or master’s program.

Every day there are a growing number of official programs being provided, and the amount of sources is almost endless. With a lot of material available, it can sometimes be hard to distinguish good from poor resources, so all of these needs to be done with care.

The goal of this article is not to list the excellent sources or to recommend any person on how to learn, nonetheless, if you’re interested, feel free to refer to our website. At ZaranTech, we offer a self-paced, online training program on Data Science, conducted by experienced subject matter experts. 

Conclusion

As always, I hope you enjoyed our article, and that I have encouraged you to think about learning Data Science or Machine Learning. If you want to find out more about Machine Learning and Artificial Intelligence feel free to refer to our blogs.