Data science is the magic behind the workings that helps social media sites to understand your preferences and create content to keep you engaged. It is also utilized by airlines to predict weather patterns and analyze the data from sensors on aircraft and rockets in order to increase the safety of flights and improve efficiency.
Understanding the significance of data is the first step towards becoming a data scientist. Having a solid foundation in programming (Python and R are the most popular) and statistics and machine learning algorithms and data visualization is essential for solving real-world issues.
The second skill is the ability to prepare raw data. This includes tasks like handling missing data, normalising features, coding categorical variables and splitting datasets into test and training sets to evaluate models. This ensures that the data is of a high standard and is ready for analysis.
Data scientists use various statistical techniques to discover patterns or trends and provide insights. These include descriptive analytics, diagnostic analytics predictive analytics, and prescriptive analytics. Descriptive analytics provides a summary of a dataset in an appealing and visually understood format, such as mean, median mode, standard deviation, and variance. This lets users make informed decisions using their findings. Diagnostic analytics makes use of previous data to predict the future. A credit card company utilizes this method to predict default risk, for instance. Predictive analytics analyzes patterns in the data that can be used to predict future trends, such as stock prices or sales.
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