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How will online learning help you to succeed in data science?

Data science is currently one of the most in-demand, rewarding, and lucrative fields in the US, with tech giants and scores of other companies battling it out to secure talented and qualified workers. A recent study by Glassdoor found that ‘data scientist’ is now the third most lucrative occupation in the country and that it commands a median base salary of more than $120,000.

The boom in data science has seen the number of job openings soar 480% from 1,700 back in 2016 to more than 10,000 today. Strong job growth is set to continue to 2030 and beyond, according to data from the US Bureau of Labor Statistics (BLS). With demand so high, there is no better way to gain the skills and experience you need to get ahead in this field than by completing an Online Master’s in Data Science at one of the oldest engineering and technology universities in the US.

While online learning has always been an excellent alternative to physically attending a university due to the flexibility it provides to busy professionals, experts at Forbes recently stated that it is now “the future of professional development”. This is because it provides a ‘focused’ learning environment where a student can access a more diverse range of tech-powered courses.

In the past, institutions often had to rely on in-person specialists to cover complex and diverse subjects, which made it difficult to deliver consistent, high levels of learning to students. Today, online learning is based on web-based solutions that offer a huge number of curated subjects, which are more accessible and cost-effective. There is even one-on-one mentorship and support for guidance throughout courses.

More specifically for data science, an online course will cover all of the fundamental skills required to succeed in this field. Data scientist Antonia Schulze, who works for Amazon Web Services in the Machine Learning Solutions Lab, says programming is one of the core skills needed to secure a role at a big tech company.

She notes: ​​“In terms of hard skills, programming knowledge — specifically R and Python — is essential. However, a basic understanding of mathematical concepts supporting data science and machine learning models is an imperative too.”

The online course will allow you to develop these skills in different computing languages such as R and Python, which are used to build data structures. These structures are crucial for the process of storing, accessing and analyzing data. You will also improve your math as online learning will cover the essential statistics and linear algebra skills that are used by data scientists on a daily basis. Calculus and algebra are essential for machine learning which allows for the automation of analytical model building.

As you progress through the course, you will soon be able to apply a wide range of tools and technologies to create and manage databases. Data preparation is another core skill — from here flows successful analysis. You will learn how to source, gather and arrange data, as well analyze large volumes of ‘big data’ and then present it in a structured way so leaders and managers can use it to improve their decisions and solve problems. 

A few of the statistical methods you will learn will help you to this end, and they will include predictive modeling, clustering and data dimension reduction. In addition to completing ‘foundations’ and ‘design core’ courses on the Master of Science curriculum, you will also get the chance to specialize in a specific area to build out your data science skills. You could learn about artificial intelligence (AI) or big data analytics, both of which will give you the skills and experience to secure job roles in this field afterwards. 

Finally, and arguably most importantly for real-world work, online learning will allow you to apply everything you have learned to come up with an implementable data-focused solution. This is something that companies value highly in the industry. Netflix is said to prioritize applicants for data roles that can use data ‘creatively’ to achieve better business outcomes. This part of the course will hone your skills and give you the freedom to solve problems in new and exciting ways. 

The final part of the online program will also see you cooperate with a sponsor or industrial partner, which is an experience that other applicants might struggle to replicate if they have not completed an accredited course. The ‘capstone experience’ will improve your communication skills too, as you will work in teams to put the tools and techniques you have learned into practice. 

Online learning will develop many of the non-technical skills required for jobs in data science. Companies will look to source workers that can apply critical thinking, problem solve proactively, and communicate effectively with other people. Collaboration is a core concept of data science as you will need to convey the results of your research to higher-ups. 

Online learning will also nurture your own intellectual curiosity, which is another skill that businesses value. You will approach the structuring of data with a drive to find answers, test initial assumptions and come up with different conclusions, as well as think on your feet and find new ways to discover more. Data scientists are usually adept at ‘parallel’ working, where they keep testing different solutions to the same problem so they only deliver the very best work.

Finally, you should view online learning as an evolving process rather than a ‘one and done’ activity as data scientists need to constantly learn and acquire new skills to succeed in this field, which is based on cutting-edge technology such as machine learning and AI. Schulze concludes: “In order to grow and thrive in this evolving scientific space, data scientists need to enjoy learning and researching new topics constantly.”

By starting a course today you can be one step closer to realizing your dream career in data science. With online learning seen as the future of professional development, you can be sure that the skills and experience you gain can be applied to the roles you eventually apply for. 

Adrian

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