Being a beginner at a point, I had issues with knowing where to start, or simply the difference between these fields. It all starts when you’re excited about starting a new career in tech, read articles on “data being the new oil”.

How exciting, you’ve decided your target niche be Machine Learning/ Artificial Intelligence. It’s all good. Until you notice sooner or later, the words are used interchangeably. With topics like : “BEST MACHINE LEARNING/DATA SCIENCE PROJECTS FOR BEGINNERS”.

Or you’re simply more than a beginner but still unsure of the Machine Learning/Data Science difference, well get in line . With a Data Science Internship and some self learning, the truth in these fields were quite clear sooner rather than later.

What is Data Science

In basic definitions, Data Science is the use of data in making predictive models. These data are analyzed, trends are discovered, and insights are drawn. The Data Scientist makes use of skill, knowledge of statistics in providing valuable charts/graphs to explain results. Data modeling and storing is the main basis of data science. Of course, these modeling, charts help in giving more advantage. These sprouts up the hot new look up: Business Intelligence .

Business Intelligence refers to the use of these data collection, application, modeling strategies in assisting businesses to make better decisions after certain sort of trends in the data are discovered. In depth data analysis and visualizations would help to give good understanding of the business next course of action and strategies.

What is Machine Learning

Machine Learning on the other hand is a subset of Artificial Intelligence that deals with making systems learn, and improve from experience. This branch of AI involves getting the data and simply using it to make predictions.

In this field, your obtained data is usually structured .From this data, you could draw insights, visualize but not as much as in Data Science. It gets even more robust when the types of Machine Learning come into play.

OKAY, BUT WHATS THE DIFFERENCE

Well here’s the fish on the hook!

While they can be similar in more ways than one, In Data Science, sometimes you will need to work on getting your data from the web (and it’s unstructured in most cases).You analyze the data, code some visualizations, get some insights on trends and use that to make a business better again. It majorly business oriented.

Machine Learning on the other hand could have a structured data in most cases. The Machine Learning Engineer could find some trends in the data to make predictions (Regression or classification).

WELL, HERE’S THAT EXAMPLE

Case Study

Someone’s made a mobile app or website. That someone feels it’s too simple and needs some automation. You’re hired and you end up getting data from a source.

Using that data, you’re able to create a Machine Learning model that can easily cluster the customers that get into the site and make purchases. That way, the model is also capable of suggesting clothes for each gender clusters (male clothes for males, female for females). Well that’s…. Machine Learning....and smart approach for customer satisfaction.

On the other hand, that someone also needs help with getting information on things like • The type of clothes they buy • The amount of time spent on the website in purchases. • The amount of purchases made in a day by customers • The reviews for some purchases made by customers.

Now that someone calls a DATA SCIENTIST to help with that. They gets data from the site through web scraping, finds trends(like why they buy these kind of clothes), visualizes these trends, gain insights, submits these statistics to the Business Owner.

Suggestions are brought up to discuss some possible changes that’ll be of good benefit to the business through the Machine Learning predictions made.

So yes, you got the difference but got a little bit confused after the mention of “Machine Learning predictions” in a Data Science task.

Data Science deals with Machine learning. While a Data Scientist may know Machine learning all the way, it isn’t always same for a Machine Learning Engineer. Hence, most “Machine Learners” end up practicing a little bit of Data Science (it’s honestly inevitable) when their goal is Artificial Intelligence.

If you’ve had a hard time understanding these terms until now, here’s your chance towards taking the right path in your career.

Pstt….Python and R are the main Languages in these fields.