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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UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
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SQL FOR DATA SCIENCE의 최상위 리뷰
This course was good because it teaches you many keywords that are used for practical application in the world of data science. I definitely feel more confident with SQL after finishing this course.
I really liked the course, I learned too much. The explanation is clear, appropriate activities and very good traceability. I really enjoyed it, I will definitely apply what I learned in my career.
Exactly what I signed up for. Basic understanding and syntax learning. For anyone looking to further their sql writing, I believe this course and the rest of the curriculum will do perfectly fine
I thought this course was great! Great introduction to Relational Databases and SQLite. Highly reccomend for anyone new to SQL, Databases, or someone looking to get started with a data science career.
Learn SQL Basics for Data Science 특화 과정 정보
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.
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