Data Science is the science focused on the study of data. It is responsible for extracting information from large amounts of data. Data Science combines statistics, mathematics, and computing to interpret data. The goal is to make decisions. Learn data science program from Prwatech data science training institutes in Bangalore at advanced level.
This data is obtained through different channels. Mobile phones, social networks, e-commerce or surveys are just some of the sources used. Our tastes, routines or movements generate data of great value for companies that want to know their customers in detail. However, the interpretation of unstructured data does not add value to companies. Hence the need for data scientists on their teams. Thanks to Data Science, companies can anticipate when making decisions. Where does the term Data Science come from? The term 'Data Science' has been around for the past three decades. But it was not until the 1970s that the term began to be used to define data processing methods. Finally, 2001 was the year that data science was introduced as an independent discipline. Is Data Science the same as Big Data? When we talk about Big Data we are referring to large volume data sets. This makes it difficult to store, manage, process and analyze it using conventional technologies and tools. In short, Big Data is responsible for solving data management and storage problems. This allows you to draw patterns and get a more complete view of customers. Prwatech is the leading Training institute for data science training in Bangalore Offering Data Science certification courses in bangalore with our Qualified Industry Certified Experts. Our python training institute in bangalore was specially designed for those who are keen to learn the python course from Scratch to Advanced level. Key concepts in Data Science There are a series of basic concepts that form data science and that we will briefly explain below. Data mining Data Mining is defined as a process used to collect and store useful data. This requires analyzing data patterns in large batches using one or more software. Thanks to this process, companies can obtain more information about their clients and develop more effective strategies. This helps them make better decisions based on information. To segment the data and evaluate it, Data Mining uses mathematical algorithms. Deep learning The goal of Deep Learning is to solve problems through neural networks that mimic brain behavior. These networks of artificial neurons are structured in layers. The first layer is where the information is captured. These data go to the next layer, in charge of performing calculations. And finally, the information collected is projected on the last of the layers. Some of the most used applications in Deep Learning are word processing and image, object or voice recognition. Machine learning First of all, it must be emphasized that Machine Learning is not synonymous with artificial intelligence. Rather, it is a concept framed within it. Fundamentally, Machine Learning is responsible for educating technology to correct mistakes on its own. It relies on prediction and classification of data to obtain useful information applicable to different areas. Artificial intelligence (AI) It is based on algorithms used to create machines that imitate human behavior. Today, emotional intelligence is applied in facial recognition or in the creation of chatbots, among others.
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