What are Artificial Intelligence and Data Science Engineering differences?

Asked by Ronak Sharma over 1 year ago

Answers 1
Avani Oswal

Avani Oswal

4th year undergrad student

The difference is significant. Both topics are heavily connected to data science and its disciples, but in tasks and studies, they differ on many levels. The first thing you need to know is that artificial intelligence (AI) and data science engineering are specializations of, say, a data science domain.

To understand the difference, you have to know what they are particularly. So basically, artificial intelligence is majorly involved with machine learning. We all know how big of a deal is machine learning in data science, right? AI is the process of identifying and developing to work independently as a machine without human interference. It learns on its own and makes decisions logically based on its findings.

Data science engineering (also called data engineering), on the other hand, is related to the engineering aspect of data science. It is responsible for creating and developing the things and elements used in data science. In simpler terms, you can say that it is like manufacturing. However, it means more than that. Data engineering generally involves data collection methods, enterprise data storage and retrieval. After these things are done, data scientists get started on the technical stuff.

So to summarize, the major difference you can state here is the approach. While AI is more like an operation and task in data science, data engineering is like creating stuff to do that. The collection, dataset design, and storages are very important to carry out tasks and operations in AI. Data engineering is in charge of that stuff. At the same time, AI is filled with programs and algorithms that are done to work faster and more efficiently.


The difference can also be seen between jobs and earrings. Though I think that's not what you meant to know when you asked the questions. Look, the answer is quite simple. North is a data science domain. One is more work while the other is creating things. AI and data engineering are among the top data science specializations. A larger number of students choose these domains in their master's program. If you are cleared on this, you can also make a decision. If you need anything, ask.


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