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WHAT IS DATA SCIENCE?

What is Data Science?                                        Data Science involves using automated methods to analyze massive amounts of data and to extract knowledge from them. There are 3 important sciences which are formed Data Science. These are: Computer Science Mathematical Statistics Applications Typical Job Duties for Data Scientists Collecting large amounts of unruly data and transforming it into a more usable format. Solving business-related problems using data-driven techniques. Working with a variety of programming languages, including SAS, R, and Python. Having a solid grasp of statistics, including statistical tests and distributions. Staying on top of analytical techniques such as machine learning, deep learning and text analytics. Communicating and collaborating with both IT and business. Looking for order and patterns in data, as well as...
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APPLICATIONS OF DATA SCIENCE

Applications of data science Data science is known for its versatility, having application in different fields that include: ECommerce Banking Consulting services Manufacturing Transportation Education Finance Movies Working as a life savior healthcare industry
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COMPONENTS OF DATA SCIENCE

 Data Science has the following components: 1. STATISTICS Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. Statistics began in the ancient civilization, going back at least to the 5th century BC, but it was not until the 18th century that it started to draw more heavily from calculus and probability theory. 2. VISUALIZATION Visualization is when we display the results of Data Science analysis in a simpler way using diagrams, charts, and graphs. It improves decision making, sense of work, customer relationship and financial performance. 3. MACHINE LEARNING Machine Learning explores the study and construction of algorithms that can learn from and make predictions on data. Closely related to computational statistics. Used to devise complex models and algorithms that lend themselves to a prediction which in commercial use is known as predictive analytics. 4. DEEP LEARNING Deep...
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