What is Artificial Intelligence? Artificial intelligence is the simulation of a human brain function by machines. Just like the human brain works on Neurons, Artificial Intelligence works on neural networks. The technology is achieved by creating an artificial neural network that can show human intelligence. Examples of AI include self-driving cars, Siri, smart homes, and many other emerging technologies.
The main human functions that an Artificial Intelligence machine performs include logical reasoning, learning, and self-correction. AI is a broad field with a number of applications but it is also one of the most complicated technology to work on. Machines are not smart intrinsically. Therefore, to make them so, we need a lot of computing power and data that will empower them to simulate human thinking.
Connection between Data Science and Artificial intelligence
Artificial intelligence and data science are the two technologies that are important for the management of information in this modern age of business. A lot of people are interested in becoming a data scientist while more and more organizations are embracing artificial intelligence. They are necessary for being competitive in this contemporary era.
- Let us now discuss what Data science It is simply the study of data and plays the role of extracting useful insights from data. Moreover, it involves developing methods of recording, storing, and analyzing data to effectively extract useful information.
- Data science works by merging various fields of computer science, scientific processes and methods, and statistics in order to extract data in automated ways. The goal of data science is to gain insights and knowledge from any type of data — both structured and unstructured. To mine big data, Data science uses a diverse range of techniques, tools, and algorithms obtained from the fields. Data science helps in the advancement of these techniques.
- There is a connection between Artificial Intelligence and Data science and the technology connecting them is called Machine Learning. Now, what does Machine Learning do?
- In machine learning, statistical methods empower machines to learn without being programmed explicitly. Machine Learning is a part of Artificial Intelligence that enables systems to automatically learn and improve from experience on their own without being explicitly programmed. It gives computers “The ability to learn” which makes them more similar to humans. This is achieved by developing computer programs that can access data and system to train themselves from that data to learn.
In general, Machine learning is designed on the basis of three key models of learning algorithms :
- Supervised machine learning algorithms
- Unsupervised machine learning algorithms
- Reinforcement machine learning algorithms
ARTIFICIAL INTELLIGENCE IN DATA SCIENCE
We will now explore what role is played by artificial intelligence in data science. It is a known fact that the data scientists use the technologies of artificial intelligence, as well as machine learning, to be able to fulfill their roles. Why are they doing it? It’s time to explore this.
a) The Role of Data Scientists
In order to understand how artificial intelligence fits in the realm of data science, it is important to have an understanding of what the data scientists do. Basically, the job of data scientist involves organizing and analyzing large amounts of data, by using the software specifically designed for the task. The final results calculated by the data scientist’s analysis needs to be easy enough for all invested stakeholders to understand — especially those working outside of IT. The job of a data scientist must not be confused with that of a data analyst, although, the two both deal with data.
b) How Artificial Intelligence Helps
By now, you should have understood that artificial intelligence is a crucial component of data science. The main objective of AI is to recreate human intelligence into computers. In turn, this can be used by data scientists to capture insights from the information that is available. Both of them rely on data. Nonetheless, it must be noted that data science does not rely only on artificial intelligence, but data science is itself an important component.
In data science, the usage of artificial intelligence and machine learning will be critical to drawing inferences and perceptions from the information present. It will help in the problem-solving task and make the most out of the data that is available. While data scientists will find their own approaches on how to solve the problem, in one way or another, artificial intelligence will act as a key component. It can help to automate various processes to change the way of how data is extracted and used in an organization.
c) Not a Replacement to Data Scientists
One thing that technology has created in humans is that it instills fear that humans are going to get replaced by these scientific or artificial intelligence machines. However, it needs to be clarified that in reality, such is not the case.
In simple words, we can say that Artificial Intelligence augments or increases the capabilities of humans. It helps in making data scientists better in what they are doing instead of replacing them. AI improves the performance of analytic technologies, breaks down the economic barriers, and improves understanding, among other things.
Summary
Artificial intelligence plays the role of an important component of data science. For some, both of them are different disciplines but they actually complement and augment each other. When these are properly utilized by today’s businesses, it is expected that there will be very significant improvements in the way the information gets managed.
The role of AI in Data science can be elaborated as :
- Artificial Intelligence recreates intelligence into computers. Whereas the role of Data science is using computers to acquire insights from data.
- Both of them are data reliant, both require you to gather, analyze, and clean a lot of data.
- Data scientists use AI to infer from data, in the form of machine learning, but they’re both big on gathering, analyzing, and collecting large amounts of data.
The role of Machine learning is to find patterns in any given type of data no matter if its an image, a collection of measurements or options to choose. Those patterns are then further used to either predict something, find clusters or to decide on equivalences.
