A computer science graduate student may be confused between the two disciplines. In fact, they usually are. But with a little effort, they can easily see the difference between the two majors. Data science is the area of science that studies information science, i.e., how it is produced, collected, and interpreted, while computer science is the field of science that studies in software engineering, which means that it is concerned with the design, development, and functionality of computer systems.
There are many similarities between these two fields. They both require broad knowledge in statistics, computer science, engineering, and software engineering. However, the similarities also show the major dissimilarity in their research areas. Data science deals more with the study of large sets of data or “big data.” Whereas software engineering mostly deals with the design of computer systems that are able to solve certain problems, or are designed to do particular tasks more quickly and efficiently than others.
The coursework for these two Masters in data science programs usually focus on statistics and data mining. Statistics deals with the analysis of statistical data, while data mining deals more with searching large sets of unprocessed data for patterns and trends. Students in this program usually specialize in one or the other area, depending on the degree program that they choose. For instance, MBA programs usually have a strong emphasis on statistics, though some do have enough courses and experience to allow them to dabble in data mining as well. However, a Master’s Degree program will put a student into a completely different career track.
The courses and experiences in a Master’s degree program focused on data science often have a bearing on the career options available thereafter. It is usually necessary to have completed an advanced degree in a scientific field to begin work in a scientific research facility. However, most companies prefer hiring those with a computer science course certification, as it proves that the person is qualified for a management position involving scientific research. These positions generally require candidates to have a good understanding of statistics and a great deal of computer knowledge.
In order to pursue work as a data scientist, students must learn how to analyze data sets and create reports that are analytically relevant to their scientific studies. There are four main areas of specialization in the field. Survey specialists are responsible for studying individual customer files. Financial analysts are responsible for creating financial reports from collected data sets, usually through a variety of data mining methods. Human resources managers are tasked with implementing strategies that maximize the productivity of employees, and are typically involved in data mining for employee scheduling and workforce performance optimization.
Students who earn degrees in these programs may also choose to specialize in a more specific area. Ph.D. candidates in human resources may choose to study how to use statistical modeling and data mining to optimize the employment practices of human resource departments. Other options for specialists include those specializing in engineering, information technology, health care, and law. Those pursuing a doctorate degree may opt to specialize in computer science, which requires a rigorous two-year coursework with an internship. Areas of study include artificial intelligence, applied computer science, statistics, and computer applications.
The field of computer science has become quite competitive over the years, due to the rise of cloud computing and its use in business. While many professionals focus on one or the other, a good data scientist can fit in a number of different capacities. Some use their skills to analyze large sets of data mined from different sources; others apply their analytics skills to applying traditional computing methods to make intuitive and intelligent decisions about what to do. With the popularity of smartphones, tablets, and other mobile devices that access the internet, the future of computing looks bright for data scientists.
Even though there is little difference between the two academic fields, there are a number of similarities. Both require hard work, creativity, and the ability to analyze and code. A data scientist with a bachelor’s degree in computer science will most likely be hired as a computer software engineer, whereas a data analyst with a bachelor’s degree in physics may find work in a variety of business fields.
