Data science is an essential field within computer science and machine learning that uses statistics, algorithms, and technology to make meaningful analysis and predictions from large amounts of data.
For instance, computer scientists often describe data science as an interdisciplinary academic field combining various tools within the computer science world to extrapolate information and meaning from large amounts of structured and unstructured data. Some of the biggest corporations and technology firms in the world have a wide variety of means for collecting and storing information related to their customers and products.
Read below to learn everything you need about data science and how it relates to artificial intelligence.
What is data science?
In the fields of finance, medicine, and e-commerce, data science analyzes vast quantities of information so that companies can make better predictions and decisions in the future. More specifically, data science is responsible for breaking down information in search of patterns so that algorithms know what to recommend to users based on prior research. For example, Companies such as Amazon and Google use data science to make recommendations to users based on their purchases and search history for potential items they may be interested in.
Data science is essential for the subfield of machine learning because it allows artificial intelligence to complete tasks typically conducted by humans. The term data science varies depending on the tasks and information that is being analyzed. The field can act as an exact science or be used as a research method as well as a discipline for professional and academic purposes. Regardless,
Concepts relating to informatics, data analysis, statistics, and mathematics, and combined in data science to find meaning within large amounts of information and analyze a data phenomenon.
What is the history of data science?
The use of the term data science originated in the early 1960s from mathematicians such as John Turkey, who was interested in the field of data analysis. At the time of its creation, using large data to make long-term predictive insights was difficult, given the technology restraints of the 1960s. However, data science started as a statistical method before evolving into the field of artificial intelligence.
Peter Naur, a Danish computer scientist, is considered the founder of the term data science and began using it back in the early 1970s as an alternative to computer science. Eventually, over time, data science began to be used to find patterns within large amounts of datasets. The process by which the field was able to evolve is due in large part to data mining and the acceleration of data storing tools.
Data science began to accelerate as a field of research within computer science as technology and commerce united. Businesses used technology to record the behaviors of their customers in order to identify future trends. Moreover, the growth of the internet made it easier for data scientists to perfect their predictive insights while businesses used it to increase profits.
How does data science relate to artificial intelligence?
Our understanding of machine learning is that it allows artificial intelligence to analyze large amounts of data and make accurate predictions based on research patterns. The algorithms that allow language learning models to compile a large essay within minutes are made possible by data science.
Companies use data science to measure the presence of their customers. For example, Netflix has an automatic AI that recommends movies and shows to users based on the characteristics found in previous areas of content that customers consumed. Artificial intelligence has helped make data processing faster and easier as well as accessible to the general public.
In the coming decades, data science will likely continue to accelerate the development of more advanced machine learning tools such as ChatGPT.