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## A Guide for the Beginners in Data Science

**What is Data Science?**

A simple and straightforward definition of data science would be the gathering of information from raw numbers. This field has contributed immensely to research, business, and many aspects of daily life. The many areas covered by science are engineering, scientific method, math and statistics, advanced computing, visualization, hacking, domain expertise, and infrastructure. Science can use both structured and unstructured data and apply the right knowledge of it across a wide range of applications. However, it is different from information or computing. He uses modern techniques and innovative tools. It uses them to get meaningful information and help in the field of research and business. The figures used to obtain information can come from various sources. They are also useful for detecting fraud by analyzing suspicious behavior and scam attempts.

**What is included in this field?**

Data science involves a number of processes that include raw data, such as analyzing a large amount of data, formulating a solution that the raw data will drive, etc. Data science also relies heavily on artificial intelligence. It helps to make certain predictions using algorithms and other machine learning techniques. In the second half of the 20th century, a scientist named Joh Tukey introduced a field called data analytics, known as data science in modern times. Some still use words like mining for the same thing. It helps in breaking down big raw numbers into small readable numbers for various businesses of different sizes ranging from medium to small and other business purposes. It uses various techniques such as logistic and linear regression, machine learning, clustering where all data is taken together, decision tree mainly used for classification and prediction, SVM known as Support Vector Machine, etc

**Why should you choose data science?**

Data science can do a lot of things. Courses use a wide range of algorithms to align raw numbers, explore various analyzes about them, help visualize collected information using graphs and tables, and help find the optimal solution to a problem by finding its root. Even though data science requires a wide range of knowledge in a different field and people with different work experiences, there are four basic areas that a data scientist should be proficient in, such as communication in the form of both verbal and written, business, and math and computer science which may include software engineering or data engineering. Science also helps industries such as airlines plan routes, schedule flights on time, and advise on what class of aircraft to buy. These are directly related to the impact on decisions about different businesses and the achievement of business-directed goals.

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