{"id":36585,"date":"2022-05-06T14:43:49","date_gmt":"2022-05-06T03:43:49","guid":{"rendered":"https:\/\/www.institutedata.com\/?p=36585"},"modified":"2022-05-16T15:36:49","modified_gmt":"2022-05-16T04:36:49","slug":"software-engineering-vs-data-science-which-one-should-you-pick","status":"publish","type":"post","link":"https:\/\/www.institutedata.com\/us\/blog\/software-engineering-vs-data-science-which-one-should-you-pick\/","title":{"rendered":"Software Engineering vs Data Science: Which one should you pick?"},"content":{"rendered":"

The global labor landscape is currently undergoing massive changes, with widespread shifts in the skills companies are demanding. Particularly, in recent years the global economy has been increasingly needing data scientists and software engineers.\u00a0<\/span><\/p>\n

This change provides individuals with the opportunity to either reskill or break into these new and emerging fields. It is an extraordinary time. The\u00a0<\/span>tech shortage and demand for skilled data scientists<\/span><\/a>\u00a0and software engineers is forcing firms and businesses to go to new levels to improve employee acquisition and retention through lucrative salaries and corporate policies, making both industries desirable and rewarding.<\/span><\/p>\n

However, for most of us, upskilling and entering a new industry is very daunting, and committing to a 3-year course can be exceedingly intimidating, not to mention expensive.\u00a0<\/span><\/p>\n

If you\u2019re still tossing up between software engineering vs data science, this article will help you narrow down which profession might be right for you.<\/span><\/p>\n

If you are already familiar with the differences between the two, click here to\u00a0<\/span>schedule a call<\/span><\/a>\u00a0with one of our consultants to discuss the study options we offer and kick-start your new career in the tech industry today.<\/span><\/p>\n

What is data science?<\/span><\/h2>\n

While it is hard to place a definition on such a rapidly evolving industry, the primary focus of data science is obtaining value from massive data sets. Originating from computer science, data science is a multidisciplinary position that involves a mixture of collecting, extracting and analyzing large amounts of data from multiple sources.\u00a0<\/span><\/p>\n

The abstract position utilizes machine learning algorithms and artificial intelligence to carry out \u2013 data purging, data mining and data transformation \u2013 all in the pursuit of providing value from data. This value is in the form of information, which gives firms and organizations a competitive edge that they otherwise may not have had.<\/span><\/p>\n

What is software engineering?<\/span><\/h2>\n

On the other hand, software engineering can be defined as the process of designing, constructing, and testing applications that will satisfy a user\u2019s needs. It is the implementation of engineering principles in the process of software development. Software engineers also may need to analyze existing applications and modify the software to meet current needs.<\/span><\/p>\n

Unlike simple programming, software engineering is primarily used for larger and more intricate software systems. These systems are used by firms in their critical processes and provide the infrastructure through which data scientists collect data.\u00a0<\/span><\/p>\n

So, what\u2019s the difference between software engineering and data science?<\/span><\/h2>\n

While software engineering and data science similarly involve extensive programming, the two careers differ in their ultimate goal. Software engineers focus on developing applications. In contrast, data scientists are more concerned with gathering and analyzing data (which is often collected through these applications).<\/span><\/p>\n

What skills are required to work as a software engineer or data scientist?<\/span><\/h2>\n

If you\u2019re looking to change careers or upskill in software engineering or data science, it is crucial to learn and master the theory and accumulate practical experience. This will make you more appealing to prospective employers, increasing your chances of gaining employment. Many courses such as ours provide students with an opportunity to create tangible work experiences through the use of student projects and capstones that can be used during the job application process as proof of expertise.<\/span><\/p>\n

As a software engineering professional you will be expected to excel from day one and be able to integrate yourself into the workplace quickly and efficiently. Traditional approaches to education are unable to offer the practical experience required and tend to only focus on underlying theory. Not only this, but most courses take over 3 years and are financially unfeasible.\u00a0<\/span><\/p>\n

As such the optimal way to start your career is through\u00a0<\/span>modern industry-focused courses<\/span><\/a>, which streamline necessary content and are focused on providing students with the tools and experience needed to launch their career in data science.\u00a0<\/span><\/p>\n

Data science is much the same. Employers expect practical experience for an entry-level position, yet most courses offer none. Lots of the traditional approaches to education take your money, your time and then leave you on your own with an out-of-date and inapplicable knowledge of theory. Here at the Institute of Data we do things differently, offering a\u00a0<\/span>comprehensive job outcomes program<\/span><\/a>\u00a0that is integrated into the course and includes one on one career coaching, resume and LinkedIn profile assistance, all of which make getting a job in your chosen sector easy and fast.<\/span><\/p>\n

Our courses offer an industry certification that demonstrates to employers that you have relevant and practical skills to excel in your new employment. Additionally, we teach students how to practically apply in-demand techniques and tools which are necessary for the workplace, as well as experience in end-to-end projects. We find this is crucial in demonstrating each individual student\u2019s ability to manage tasks that they will be faced with in the real world.\u00a0<\/span><\/p>\n

So, which one should you pick?<\/span><\/h2>\n\n\n\n\n\n\n
Data Science<\/span><\/strong><\/td>\nSoftware Engineering<\/span><\/strong><\/td>\n<\/tr>\n
Are you creative and do you enjoy solving problems?<\/span><\/td>\n\u00a0Are you interested in analyzing user needs, and then designing, building and testing suitable software applications?<\/span><\/td>\n<\/tr>\n
Do you find mathematics and statistics interesting?<\/span><\/td>\nAre you methodical and process-driven?<\/span><\/td>\n<\/tr>\n
Are you interested in analytics, machine learning, and artificial intelligence?<\/span><\/td>\nAre you interested in coding?<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u00a0<\/span><\/p>\n

Whichever career path you choose to go down, you will be at the forefront of a technological revolution and make an impact on the world around you. Take advantage of this opportunistic time in tech, and\u00a0<\/span>schedule a call with one of our course consultants<\/span><\/a>\u00a0to discuss your study options today.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

The global labor landscape is currently undergoing massive changes, with widespread shifts in the skills companies are demanding. Particularly, in recent years the global economy has been increasingly needing data scientists and software engineers.\u00a0 This change provides individuals with the opportunity to either reskill or break into these new and emerging fields. It is an…<\/p>\n","protected":false},"author":1,"featured_media":36579,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[539,527,532,530,531,542],"tags":[],"class_list":["post-36585","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bigdata","category-careerchange","category-datascience","category-datasecurity","category-dataskills","category-softwareengineering"],"_links":{"self":[{"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/posts\/36585","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/comments?post=36585"}],"version-history":[{"count":0,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/posts\/36585\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/media\/36579"}],"wp:attachment":[{"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/media?parent=36585"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/categories?post=36585"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.institutedata.com\/us\/wp-json\/wp\/v2\/tags?post=36585"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}