Data Science and Artificial Intelligence (AI) are two different fields that use data for different purposes. While Data Science extracts knowledge and insights from data for informed decision making, Artificial Intelligence uses AI models that are trained on large data sets to learn patterns from data, make predictions, and perform tasks on their own. Due to their ability to learn, make predictions, perform tasks, solve problems and make decisions, AI models are used for building intelligent AI systems that can perform tasks that usually require human intelligence. By performing tasks autonomously, they help save time and effort of humans.
When it comes to the use of techniques, data science uses algorithms, scientific methods, and systems to extract knowledge and insights from structured and unstructured data. In terms of techniques used, AI systems utilize machine learning, natural language processing, and computer vision to process information, learn and perform tasks autonomously.
The core process of data science involves the collection of data followed by cleaning, analysis, and visualization of data to uncover insights from past data. The core process of artificial intelligence revolves around developing algorithms and models that enable machines to think, learn, and act on their own.