We live in a technology-driven world. Everything and Everyone depends on technology in one way or other. Various fields make up the technological industry.
They form the basis of innovations and technology. Artificial intelligence and data science are two of the important branches of technology that contribute a lot to modern innovations.
Key Takeaways
- Artificial Intelligence focuses on developing intelligent systems that can simulate human decision-making, while Data Science deals with extracting insights from large datasets.
- AI requires extensive algorithms and programming language knowledge, whereas Data Science emphasizes statistical and analytical skills.
- AI systems can learn and adapt over time, while Data Science primarily analyzes past data to make predictions.
Artificial Intelligence vs Data Science
The difference between Artificial intelligence and data science is that artificial intelligence gives machines the ability to work as autonomous bodies on the other hand Data science deals with data. Data is crucial for many companies to manufacture things that are in demand and will be preferred by customers. Artificial intelligence is used to create machines that are used for data processing.
Artificial intelligence was created to mimic the natural intelligence of living organisms. But, it is given to machines and robots. The machines with this technology can act on their own depending on the surrounding.
This technology is widely incorporated in new inventions. Vacuum cleaners, refrigerators, and automobiles with artificial intelligence are being marketed. People prefer appliances with this technology because it reduces time and work.
Data science is the unification of statistics, Informatics, and data analysis to understand the unknown real facts or phenomena. Theories from various fields including mathematics, statistics, computer science, etc are considered in data science.
It is one of the emerging fields and data scientists are in demand. Data scientists must be multi-talented so that they can interrelate and analyze different things.
Comparison Table
| Parameters of Comparison | Artificial Intelligence | Data Science |
|---|---|---|
| Tools | Shotgun, Tensorflow, PyTorch, Kaffe, etc | Python, R, SAS, SPSS |
| Function | To create machines with autonomy and cognition | To analyze and find a hidden pattern in data |
| Type of data | Standardized | Structured or unstructured |
| Application | Healthcare, Robotics, Transport | Marketing, advertisement |
| Scope | Implementation of algorithms to get the desired outcome | Data operations are carried out |
What is Artificial Intelligence?
Artificial intelligence was made a discipline of academics in the year 1956. Since then this field has faced support as well as criticisms. Lack of findings was also a major crisis for research in this field during early times.
Many new approaches have been tried and many worked out but few like imitating the function of human brains in problem-solving and animal behavior has been discarded.
The machines manufactured using this Artificial intelligence technology are designed in ways to have some special features like moving automatically, perception, language recognition, etc.
Problem-solving techniques are also incorporated into new artificial intelligence inventions. The principal goal of Artificial intelligence was to make machines with the ability to act like human minds.
Artificial intelligence has wide application today. It is found in search engines like Google.
Recommendation systems of Streaming platforms like Netflix and Amazon prime also use artificial intelligence to recognize the user’s choice on movies and web series and to recommend them similar movies.
Amazon’s Assistant Alexa and Apple’s Siri are also developed by artificial intelligence. Face recognition is used in mobiles, and spam filtering includes artificial intelligence.
Games are also including artificial intelligence to provide users with an amazing experience.
It is also used to make art like paintings and poetry, prove theorems of maths and physics, in biochemistry to identify the structure of protein within a short period.
Procedures that took years to complete and identify the protein structure have been made easy with artificial intelligence.
What is Data Science?
Data science is a combination of many fields. Data sets are big collections of data, these data sets are used to solve various problems arising in different fields.
The data set is prepared for analysis, then the problems are formulated and the solutions are found by analyzing the data. Fields like Information science, statistics, mathematics, graphic design, business, communication, etc are part of data science.
The term data science was initially used as an alternative for statistics by Jeff Wu. Some people have used it as a substitute for computer science but many have disagreed.
Many scientists still believe that data science is not a different field but just another name for statistics. The relationship between data science and statistics remains controversial.
The earlier application of data science was in finance. Data scientists were appointed to help companies decrease the loss they face.
This applied to banking companies where the data scientists divided data depending on customer profile, and other features. In medicine, data science was used in the procedure of tumor detection and texture identification.
In fields like genomics, data science has been useful in the research of personalized medicine discovery. Drug discovery was a tiresome process in the past but, now it has been simplified with the help of data science and machine learning.
Data science is used to predict the success percentage of a drug. This has an immense effect on the pharmaceutical industry.
Main Differences Between Artificial Intelligence and Data Science
- Artificial intelligence is implementing a model that had been designed to carry out specific functions while data science consists of analyzing data collection to find a solution
- Artificial intelligence is formed by computer algorithms, whereas data science makes use of various statistical, mathematical, and computer-based techniques
- Artificial intelligence is a complex field but it is considered simpler than data science. Data science involves multiple tools and steps to come to a conclusion which can be cumbersome
- Artificial intelligence gives the models the ability to function autonomously. But, the main goal of data science is to find the patterns hidden in data so that it can be used in a beneficial way
- Human cognitive understanding is used as the inspiration in Artificial intelligence while data science is about making models using statistics.
Last Updated : 13 February, 2024
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Sandeep Bhandari holds a Bachelor of Engineering in Computers from Thapar University (2006). He has 20 years of experience in the technology field. He has a keen interest in various technical fields, including database systems, computer networks, and programming. You can read more about him on his bio page.
