As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.
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Лучшие отзывы о курсе SQL FOR DATA SCIENCE
Videos are a bit lengthy course could be shorter by 10-20% from a time perspective with the content staying the same. Overall good course for anyone that need to learn or to refresh their skills.
Honestly it's not obvious why it is called sql for DATA SCIENCE. In my opinion it's just SQL Basics.\n\nIt's pity that there weren't window functions.\n\nBut generally the course is good enough.
A comprehensive course that covers major aspects of query building and retrieval in a management system. The topics were delivered well and the materials/assignments were relevant for skill-building.
Did not need to be a peer review assessment, most of the tests lacked creativity and could be automated. The peer review component should just apply to the creative components that can be expanded.
Специализация Learn SQL Basics for Data Science: общие сведения
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оформив подписку на специализацию?
Можно ли получить финансовую помощь?
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