Hello,

To begin with, it is impossible to compare the two realms in order to determine which is superior — exactly because they are two distinct fields of study. It's the equivalent of contrasting science with the arts. However, the clear popularity of data science nowadays cannot be denied. Almost every industry has turned to data to help them make better business decisions. Whether it's for performance analysis or device data-powered plans or apps, data has become a vital element of enterprises. Machine Learning, on the other hand, is still a developing field that has yet to be accepted by a few businesses, implying that ML technologies will become more in demand in the near future. As a result, specialists in both of these fields will be in high demand in the future.

Because Machine Learning and Data Science are so intertwined, a fundamental understanding of both is essential to specialise in one of the two fields. To begin with Machine Learning, however, understanding of data analysis is necessary in addition to data science. Understanding and cleaning data before using it to create ML algorithms necessitates learning computer languages such as R, Python, and Java. Tutorials on these programming languages, as well as basic data analysis and data science ideas, are included in most Machine Learning courses.

Data Scientists or Machine Learning Engineers make greater money.

Data Scientists and Machine Learning Engineers are both in high demand in today's industry. When it comes to entry-level positions, data scientists appear to make more money than Machine Learning engineers. For entry-level positions in data science, the average income is more than 6 LPA, whereas for Machine Learning engineers, it is approximately 5 LPA. Senior specialists, on the other hand, make almost the same amount in both disciplines, averaging approximately 20 LPA.

Hope this helps.