Data science is an interdisciplinary field that extracts valuable information from data useful for business. From data analysis, cleansing and wrangling to the interpretation of patterns, it turns noisy, structured and unstructured data with the use of statistics, algorithms and procedures & other tools. It combines tools, methods, and technology to generate meaningful information from data. Modern organizations are inundated with data; there is a proliferation of devices that can automatically collect and store information. Data science allows businesses to uncover new patterns and relationships that have the potential to transform the organization.
FOUR STAGES OF DATA SCIENCE
Therefore data scientists need a strong knowledge of computer programming, data analytics, artificial intelligence (AI), and predictive analytics. They create the applications and machine learning algorithms that transform raw data, assist with business decision making, and power scientific discovery.
In this course:
Describe common Python functionality and features used for data science