In the world today, two technologies are transforming everything: data science and artificial intelligence. They’ve been the talk of the digital town for a few years now.
Many people use terms like data science and artificial intelligence interchangeably, but they do not operate data science operations; AI is not entirely integral to data science.
This article will discuss the basics of the two technologies and what makes them different from each other.
Data Science
Data Science involves the process of analyzing unstructured data to generate valuable insights using various tools. In data science, multiple steps and procedures are involved in extracting, manipulating, mapping, visualizing, and maintaining data to predict future events.
It is a multidisciplinary field that has main components like Mathematics, Statistics, and Programming. It is generally expected that a data scientist has extensive knowledge of many concepts and technologies, including machine learning algorithms and artificial intelligence.
It is said that a new industrial revolution is underway thanks to data science. Companies like Airbnb, Amazon, Netflix rely heavily on Data science.
Artificial Intelligence
Often called AI, artificial intelligence consists of complex computer algorithms that emulate human intelligence. It makes machines smart. A computer program that uses artificial intelligence will learn as it goes, gaining expertise at solving specific types of problems as it accumulates data.
It builds a solution to a problem using principles of software engineering and computation algorithms. Organizations as large as Facebook, Amazon, and Google rely heavily on artificial intelligence.
Difference between Artificial Intelligence and Data Science
It is important to note that AI implements a predictive model for foreseeing events, while data science involves pre-processing, analysis, and prediction. AI uses the same data in machines that are collected, curated, and analyzed through DS.
A data science approach utilizes statistical, design, and development methods, while artificial intelligence focuses mainly on algorithm design, development, efficiency, conversion, and installation of these designs.
By using data science, you can uncover patterns and trends within data and derive statistical insights. In contrast, artificial intelligence is used to handle data autonomously to eliminate the need for a human to manage the entire process.
DS uses more tools than AI. This is because several steps are involved in data science to analyze data and find insights.
Data Science makes use of tools, such as SAS, Apache Spark, SPSS, Keras, R, Python, etc., while AI uses tools viz. Shogun, Theano, Keras, PyTorch, TensorFlow, Scikit-Learn, etc.
Many industries such as healthcare, transportation, robotics, automation, and manufacturing use AI applications. On the other hand, applications based on data science are used in Internet Search Engines like Google, Yahoo, Digital advertisements, Marketing fields, Image/Speech recognition, Banking, Gaming, and many more.
There’s a difference in the degree of scientific processing as well. Comparatively to Data Science, Artificial Intelligence uses a higher degree of scientific processing.
Conclusion
Artificial intelligence is a broad area that is still in its infancy and is mainly unexplored. In contrast, a substantial change has already been made in the market and our lives thanks to data science. The central point to note is that Data Science uses artificial intelligence to develop predictions and analyze and visualize data.
AI and data science go hand in hand in today’s industries. The application of Data Science empowers them to make on-the-fly decisions and assess their performances. At the same time, Artificial Intelligence helps industries maintain efficiency, minimize workload, and speed up their processes to innovate more efficiently.
