Difference Between Data Science and Machine Learning

Many people believe that data science is primarily about ML and that the job of a data scientist is primarily to create and train ML models. Most people think like this because they don’t know what the difference is between them. So in this article, I will explain the difference between data science and machine learning to you.

Difference Between Data Science and Machine Learning

Data science is all about understanding business problems using data. It starts with collecting data, then understanding the data, cleansing and transforming it, and then we make decisions about the future course of action. Machine learning is like an afterthought after the full process of data science.

Also, Read – 100+ Machine Learning Projects Solved and Explained.

But one thing to understand here is that ML is one of the most essential thoughts in the entire process of data science.

So when we are working with data to make future decisions on a business strategy, it is data science. So far you must have some idea that ML is part of data science, but why do we have a separate term for it? If ML is a concept of data science, why is it just as important as data science?

Data Science Vs. Machine Learning: Examples

The main difference between data science and machine learning is that in data science we study the problems of a business and make decisions based on our observations, where ML is used to create and use models that can learn from the data. Simply put, machine learning can also be called predictive modelling.

In Data Science we analyze a business using data, but in ML our main goal is to create models to predict future outcomes on new data. Some of the examples of using machine learning models are as follows:

  1. Predict whether an email is spam or not
  2. Predict fraud transactions
  3. Predicting which ad to show to which user
  4. Predicting the next world cup winner.

Now let’s take a look at examples of the same business model to see where we use data science and where ML. The popular dating app “Tinder” collects data from its members to find the most suitable match for them. At this point, Tinder is using data science. But if we start analyzing the data to predict how okay someone is to sleep with you on the first date, then at this point Tinder is using machine learning.


Hope you now understand what is the difference between data science and machine learning. Data science is used to analyze and make business decisions, where ML is used for predictive modelling using the same data.

I hope you liked this article on the difference between data science and machine learning. Feel free to ask your valuable questions in the comments section below.

Aman Kharwal
Aman Kharwal

I'm a writer and data scientist on a mission to educate others about the incredible power of data📈.

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