Artificial Intelligence And Data Science

Artificial Intelligence And Data Science: key Differences Between The Two

Technology engirds the entire earth in which we are currently living. Have you ever imagined how it would be like to survive in the pandemic if there would be no technology?  

In this modern age when information is all around, artificial intelligence and data science are the most evolving technologies in this tech-oriented world. DS is just a term that comes under the umbrella of artificial intelligence, which means that it does not entirely represent AI.  DS utilized AI in its operations. 


This piece of content talks about the crucial concepts of AI and DS that everyone should know to keep up their competitive edge in this ever-evolving world. 

Before jumping into the key differences between these two revolutionary technologies, let’s just find out what is artificial intelligence and data science in layman’s terms. 

So without further adieu, keep the ball rolling. 

What is Artificial Intelligence? 

As the name suggests, the intelligence that machines of this modern age possess is called artificial intelligence. Scientists and developers are constantly researching and striving to make machines intelligent just like human beings. AI makes the utilization of algorithms to carry out autonomous actions. 

Recently, some major technology giants such as Facebook, Amazon, and Google are leveraging AI to create autonomous systems. Several traditional AI algorithms precisely offered goals, just like the case of path-finding algorithms, for example, A*. Perhaps, contemporary AI algorithms, such as deep learning, understand the patterns and discover the goal which is embedded in the data. 

What is Data Science? 

Data science is the most evolving technology that has conquered several industries across the globe. The advent of this technology has resulted in the fourth industrial revolution in the present world. That’s the result of the contribution of a ginormous eruption in data and the growing requirement of the modern industries to depend on data to develop better products. We all are a part of a data-driven society. Data has become a crucial requirement for several industries for decision-making and several other purposes. 

Now that you have a rough idea of what these technologies are, let’s glide into the key differences between data science and artificial intelligence. 

Key Differences 

Without the shadow of any doubt, DS and AI can be used interchangeably, but still, there are a couple of differences between the two fields. 

Let’s start exploring the key differences between AI and DS. Stick with us. 

Artificial Intelligence is a Useful Tool for Data Scientist 

AI is not more than a tool or a procedure for a data scientist. They prefer this procedure over other methodologies and use that procedure for the analysis of data. Maslow’s Hierarchy analogizes it in the best possible way. In that hierarchy, every component of the pyramid depicts a data operation that Data Scientists perform. 

Artificial Intelligence And Data Science
Several requirements and roles of the company also highlight the major differences between data science and machine learning. For instance, innumerable companies need pure AI positions to stay competitive, such as NLP Scientist, Machine Learning Engineer, Deep Learning Scientist, and so on. Such scientists and engineers are required for developing products that are completely based on AI. Many of such roles need DS tools such as Python or R to carry out several data operations and also require additional computer science expertise. 

On the flip side, a data scientist is responsible for extracting data with the help of NoSQL and SQL queries, analyzing the patterns in data, cleaning several anomalies in the data, and applying predictive models to sow the seed of future insights. Moreover, data scientists also use AI tools such as deep learning algorithms on the basis of requirements for the prediction of the data and perform relentless classification. 

Constraints for Contemporary Artificial Intelligence  

Contemporary AI utilized in the current world is the “Artificial Narrow Intelligence.” Under this form of artificial intelligence, computer systems do not have complete consciousness and autonomy, just like human beings. Instead, they can only perform tasks for which they are trained.  

For example, an AlphaGo probably is able to defeat the Globe’s number 1 Go champion, but he will not know that it is playing the game of AlphaGo. This means that he does not have a conscious mind. 

Data Science is an All-Inclusive Procedure 

As the name suggests, DS is the analysis and study of data. The responsibility of a data scientist is to make decisions that prove to be advantageous to the company. In addition, the role of the data scientist varies from industry to industry. The main requirement of data scientists in their everyday roles and responsibilities is to preprocess data. Preprocessing data refers to performing data cleaning and transformation. After that, data scientists analyze the patterns in the data and utilize visualization techniques to draw graphs that highlight the analytical procedures. Then he develops prediction models that find the probability of the occurrence of approaching events. 

Key Takeaways 

At the heart of it all, the following are the key takeaways of this piece of content. Let’s flick through each one of them. 

  • Data science does not require intense scientific processing in comparison to artificial intelligence. 
  • Scientists and engineers build models that use statistical insights with data science. On the flip side,  scientists and engineers build models that emulate cognition and human understanding with AI. 
  • Data science refers to finding hidden patterns in the data. At the same time, artificial intelligence refers to imparting autonomy to the data models. 
  • DS involves various tools in comparison to artificial intelligence. The reason for this is DS involves several steps for analyzing data and then generating insights with the help of that data. 
  • Data science consists of several statistical techniques, whereas AI utilizes computer algorithms. 
  • Data science is an all-inclusive process that comprises prediction, visualization, analysis, and pre-processing. 

Hence, businesses and individuals of this modern age should have knowledge of these ever-evolving technological innovations and advancements. Needless to say, technological evolution has completely revamped the world in which we are currently living. These are here to stay and are not going anywhere anytime soon.

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