Introduction To Data Science | 468 MB
Introduction to Data Science provides a comprehensive overview of modern data science: the practice of obtaining, expling, modeling, and interpreting data. While most only think of the "big subject," big data, there are many me fields and concepts to exple. Here Barton Poulson exples disciplines such as programming, statistics, mathematics, machine learning, data analysis, visualization, and (yes) big data. He explains why data scientists are now in such demand, and the skills required to succeed in different jobs. He shows how to obtain data from legitimate open-source reposities via web APIs and page scraping, and introduces specific technologies (R, Python, and SQL) and techniques (suppt vect machines and random fests) f analysis. By the end of the course, you should better understand data science's role in making meaningful insights from the complex and large sets of data all around us.
* The demand f data science
* Roles and careers
* Ethical issues in data science
* Sourcing data
* Expling data through graphs and statistics
* Programming with R, Python, and SQL
* Data science in math and statistics
* Data science and machine learning
* Communicating with data.
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