As the data science industry grows and changes, more students and professionals are thinking about new ways to develop their skills and build a portfolio of projects that help them stand out from the crowd. By supplementing traditional data science skills with proficiency in other Science, Technology, Engineering, and Mathematics (STEM) fields, beginners and experts alike can differentiate their resumes from others. Since data science tools are a necessity at every stage of working in the industry, one of the key components of the field is understanding the websites and software that are commonly used and developed.
To develop this understanding, Data Scientists can create their own websites and applications. Software engineering is a broad industry that offers students and professionals in the field the opportunity to develop a toolkit of skills, from computer programming to product development. Learning software engineering requires you to apply your knowledge of programming languages and database design to dynamic projects, and any Data Scientist would benefit from learning the skills of software engineering.
What is Software Engineering?
Software engineering is an industry that utilizes the methods and techniques of engineering in order to develop software, application, and programs. As the name suggests, software engineering exists at the intersection of product development and programming. Many Software Engineers specialize in the development of specific products or become engineers who utilize a few key programming languages. Over time, the development of software has also drawn from Agile principles that emphasize the importance of testing, iteration, and efficiency.
This focus on Agile software development is also represented through an increased focus on platform users and software consumers. By focusing more on users, software engineering is not only about the back end development of a project but also thinking about how consumers will engage with that product once it has been delivered to market. This engagement, along with user experience research, can be used to make improvements or changes to the software. Including more Agile principles in the development of software also means that software engineering engages in many of the same steps and stages of the data science lifecycle. Data scientists who are new to the field can easily catch on to the cyclical process of working to develop and present a deliverable.
How Data Scientists Can Apply Software Engineering
When working within a team or a technology company, it is also common for Engineers and Data Scientists to work together, so it is useful to have a shared language and understanding of both within any STEM field. Similar to data science, much of software engineering is focused on learning how to work with data through advanced training in specific programming languages, software libraries, and database management tools.
One of the ways that software engineering can help set apart your resume as a Data Scientist is through learning languages and practical skills which are not always common within the training and curriculum for data science. Once you learn those skills, it will be possible to develop a portfolio of projects and applications which demonstrate this overlap between software engineering and data science.
Python, Java, and C++
When pursuing a career in software engineering or adding software engineering skills to your data science toolkit, there are a few key languages to learn. Python is a go-to for engineering because it includes a series of skills that are useful when developing products and gathering data on users. For example, Python is known for its machine learning and automation capabilities, so utilizing this language is useful when running product tests or checking for bugs in a system. In comparison, Java is more commonly used for the development of websites and offers features that make it easier to design applications and HTML pages.
C++ is also commonly used when developing applications, games, and platforms. As a general-purpose language, C++ is very versatile and serves as the foundation for many other languages and programs. Each of these languages is especially useful when developing a product from start to finish. For Data Scientists who are incorporating more engineering into their skillset, knowing these languages and developing software prototypes or data models with them is an excellent addition to your professional portfolio.
Software Libraries and Frameworks
Open-source programming languages are known for their communities of Data Scientists and Developers who contribute to resources, such as libraries and packages. While data science has its own libraries within programming languages like Python, many of the same libraries which are useful to Data Scientists are also utilized within software engineering. In addition, there are many software-specific libraries and frameworks that Data Scientists can use to develop their own unique projects and to learn more about the field. Apache Hadoop is one of many examples.
SQL, NoSQL, and Database Systems
Another useful skill for both Data Scientists and Software Engineers is an understanding of database management and systems. Many Data Scientists develop a familiarity with databases by collecting and organizing a dataset during a research project. For Software Engineers, database design and management are essential to working in the back end of website, application, and platform development. There are several programming languages that are used to develop and query databases. Whether it is SQL relational database management systems or one of many NoSQL databases, knowledge of Python, the SQL programming language, and even Java are all useful to building a repository for collecting and storing information and data.
Interested in learning more about Software Engineering?
Noble Desktop offers a variety of data science classes, including programs and workshops for beginner and more advanced Data Scientists and Software Engineers. The Data Science Certificate is geared towards beginner Data Scientists and prospective Python engineers. In this course, students some of the most popular programming languages in the field.
From the collection and organization of data to the visualization and sharing of key insights and information, Data Scientists employ many of the same skills and tools as Software Engineers and Software Developers. The Software Engineering Certificate is a go-to for students who want to explore programming languages such as JavaScript, as well as front end and back end development of websites. Whether you are a Software Engineer interested in expanding your data science skills or a data science professional making the transition into a software engineering role, Noble Desktop offers courses and certificate programs for you!