Data science and artificial intelligence are two technological advancements and skill-based career paths that have caught the world by storm. They are often used interchangeably in a conversation, but one does not define the other. Data science is known to employ AI in its operations and the foundation of artificial intelligence is structured and unstructured data. Despite being closely intertwined, data science and artificial intelligence have differences that set them apart from each other. This article shall give an overview of the differences between data science and artificial intelligence.
What is Data Science?
Data science, at its core, is the art of using various tools, algorithms, and machine learning principles to analyze and decipher hidden patterns from raw data. Recent years have witnessed a massive explosion in data and the way data is being acquired. This data has become a key driver in the way industries are run, and industries have understood the importance of data when it comes to key decision-making and product releases. It’s this massive change in trend that has led to data science being a crucial part of the modern world.
A data scientist must be proficient in the extraction, manipulation, visualization, and maintenance of data. There are various subfields in data science such as mathematics, analytics, and programming, and it’s the proper amalgamation of these subfields that give rise to well-endowed data scientists. Data scientists should also have prior knowledge of languages such as C, C++, Python, and R and should also be familiar with Machine Learning techniques. (Read more on: Careers opportunities in Data Science)
What is Artificial Intelligence?
Artificial Intelligence, put simply, is intelligence possessed by machines. It is usually modeled after natural intelligence seen in humans and animals. AI, ideally, can simulate human intelligence in machines, giving rise to a whole new way in which autonomous tasks can be carried out. Data Science and artificial intelligence complement each other, with data science employing artificial intelligence to give better, more accurate analysis and results.
Artificial intelligence engineers focus on deep learning practices, the research of new algorithms, the employment of neural networks, and the integration of AI solutions within a company. Although similar in the job description, artificial intelligence engineers and data scientists have to access different libraries for each role, changing the way that each carries out their designated tasks. (Read more on: Difference between AI and ML)
Difference between Data Science and Artificial Intelligence
Data science and artificial intelligence share certain similarities, but have varying degrees of differences when it comes to other aspects. Let’s take a look at how these technological marvels are different from one another.
Data science and artificial intelligence are used in numerous industries and have wide applications. Artificial Intelligence, albeit being still developed, is used in various industries such as healthcare, transport, automation, and robotics. Data Science applications are more prominently used by internet search moguls such as Google and Bing, and in the marketing, advertising, and banking industries. (Read more on: 5 Real world applications of Python)
Artificial intelligence was created with the purpose of simulating human intelligence in machines, in turn giving them the ability to carry out higher-order tasks. Data science has been employed with the true goal of finding patterns within massive hordes of data and then using these patterns to come up with optimal solutions for problems. These varying purposes set them apart from each other.
The tools used by artificial intelligence engineers are Mahout, Shogun, TensorFlow, PyTorch, Kaffe, and Scikit-learn. Data scientists often use tools such as eras, SPSS, SAS, Python, and R.
Degree of Scientific Processing
Artificial intelligence is known to use a high degree of scientific processing to emulate human intelligence and to carry out autonomous tasks. Data science on the other hand uses a comparatively lesser degree of scientific processing to analyze and decipher data.
Data science and artificial intelligence are two complementary fields, with artificial intelligence being a broad horizon with much left to be explored. Data Science has long since made its mark in the world and data scientists are widely sought after to this day. We at Praxis are proud to offer a Post Graduate Program in Data Science that will train and equip you with all the tools necessary to make it large as a data scientist. Our 9-month long PGP in Data Science comes with an accomplished placement record and gives you insight into the workings of various industries and instances, allowing you to have an early edge over your competitors.