University of California, Davis

SQL for Data Science

Sadie St. Lawrence

Instructor: Sadie St. Lawrence

632,970 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(16,524 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 15 hours
Learn at your own pace
91%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.6

(16,524 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 15 hours
Learn at your own pace
91%
Most learners liked this course

What you'll learn

  • Identify a subset of data needed from a column or set of columns and write a SQL query to limit to those results.

  • Use SQL commands to filter, sort, and summarize data.

  • Create an analysis table from multiple queries using the UNION operator.

  • Manipulate strings, dates, & numeric data using functions to integrate data from different sources into fields with the correct format for analysis.

Details to know

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Assessments

14 assignments

Taught in English

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This course is part of the Learn SQL Basics for Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

In this module, you will be able to define SQL and discuss how SQL differs from other computer languages. You will be able to compare and contrast the roles of a database administrator and a data scientist, and explain the differences between one-to-one, one-to-many, and many-to-many relationships with databases. You will be able to use the SELECT statement and talk about some basic syntax rules. You will be able to add comments in your code and synthesize its importance.

What's included

11 videos3 readings4 assignments2 discussion prompts

In this module, you will be able to use several more new clauses and operators including WHERE, BETWEEN, IN, OR, NOT, LIKE, ORDER BY, and GROUP BY. You will be able to use the wildcard function to search for more specific or parts of records, including their advantages and disadvantages, and how best to use them. You will be able to discuss how to use basic math operators, as well as aggregate functions like AVERAGE, COUNT, MAX, MIN, and others to begin analyzing our data.

What's included

9 videos1 reading3 assignments

In this module, you will be able to discuss subqueries, including their advantages and disadvantages, and when to use them. You will be able to recall the concept of a key field and discuss how these help us link data together with JOINs. You will be able to identify and define several types of JOINs, including the Cartesian join, an inner join, left and right joins, full outer joins, and a self join. You will be able to use aliases and pre-qualifiers to make your SQL code cleaner and efficient.

What's included

10 videos2 readings3 assignments1 discussion prompt

In this module, you will be able to discuss how to modify strings by concatenating, trimming, changing the case, and using the substring function. You will be able to discuss the date and time strings specifically. You will be able to use case statements and finish this module by discussing data governance and profiling. You will also be able to apply fundamental principles when using SQL for data science. You'll be able to use tips and tricks to apply SQL in a data science context.

What's included

11 videos3 readings4 assignments1 discussion prompt

Instructor

Instructor ratings
4.7 (4,656 ratings)
Sadie St. Lawrence
University of California, Davis
4 Courses645,688 learners

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