Advanced SQL for Data Science: Time Series
With Dan Sullivan
Liked by 1,484 users
Duration: 1h 20m
Skill level: Advanced
Released: 4/26/2019
Course details
Time series data is data gathered over time: performance metrics, user interactions, and information collected by sensors. Since different time series data have different measures and different intervals, these data present a unique challenge for data scientists. However, SQL has some features designed to help. This course teaches you how to standardize and model time series data with them. Instructor Dan Sullivan discusses windowing and the difference between sliding and tumbling window calculations. Then learn how SQL constructs such as OVER and PARTITION BY help to simplify analysis, and how denormalization can be used to augment data while avoiding joins. Plus, discover optimization techniques such as indexing. Dan also introduces time series analysis techniques such as previous time period comparisons, moving averages, exponential smoothing, and linear regression.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
-
Showcase on your LinkedIn profile under “Licenses and Certificate” section
-
Download or print out as PDF to share with others
-
Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 5 quizzes
- Learn on the go Access on tablet and phone
Download courses
Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection.