**Introduction**

Data Science is a broad field that focuses on extracting knowledge from data using techniques like statistics, data analysis, and visualization. Machine Learning is a subset of data science that uses algorithms to allow systems to learn from data, make predictions, and improve over time without being explicitly programmed.

First, let’s understand the meaning of the two terms and their implications individually, then we shall discuss their difference on various bases to get more clarity.

Also, see - __Locally Weighted Regression__.

**What is Data Science?**

__Data Science__ refers to the complicated study of the massive amounts of data stored in a company’s or organisation’s repository. It includes tracking the origin of the data, the exact study of its content, and using it to accelerate the growth of the firm.

Data Science includes the entire process of data extraction, data visualisation, data cleansing and data analysis. The data stored in an organization’s repository can be grouped into two categories – Structured and Unstructured.

After analysing these data sets, data scientists interpret some information that can be used to derive market trends, this helps the business in generalising the consumer’s activity and noting their response towards the various price fluctuations and product changes for future reference.

**Data Analyst Vs Data Scientist**

Data scientists are experts who put raw data into use for handling crucial business matters. Data Scientists have a thorough knowledge of coding paradigms, numerical computation, statistics, and graphical representation of data for carrying out data visualisation and extraction.

The applications of Data Science have tremendously increased over the last few years, it is widely being used by companies such as Amazon and Netflix for generating recommendations for users. __Data science__ is also widely used in the fraud detection sector, search engines, airline and banking software, the healthcare sector and so on.

**Skills Required to Become Data Scientist**

There are several skills that are required to become a Data Scientist:

**Programming Language:**You should be good at programming language, there are some programming languages which are preferably used for data science such as Python, R, SQL, Scala, and JavaScript. This is a very basic skill to have in order to become a data scientist.

**Statistics and Probability:**While or After learning a programming language, you can read about statistics and probability because you will need to organize and present the data and this skill will help you a lot.

**Linear Algebra and Calculus:**You should be familiar with the mathematics topics such as linear algebra and calculus because while developing algorithms you may face problems if you are familiar with these topics.

**Data Visualization Tools:**You can learn the data visualization tools such as Power BI, Tableau, or Python libraries like matplotlib.

There are skills you can learn but you should always learn those skills while exploring the field of data science. You can also consider enrolling in our data science course to sharpen your skills and stay competitive in the tech industry.