Intermediate Flux
Intermediate Flux Tutorial Course for Essentials on Time Series Data
Intermediate Flux Tutorial Course for Essentials on Time Series Data
6-9 hours

Intermediate Flux Tutorial Course

Course Description
In this course you will take your Flux skills to the next level through a combination of real-world sample problems and video lectures. In the first section of this free course, you will learn about Flux window functions and how they can be used for aggregating data as well as creating moving averages. In the next section, you will learn about the Flux map function and how you can use it to create custom functions using conditional logic. In the third section of the course, you will learn how to join streams of data together using Flux, some real-world reasons you would want to do this, and go over some example problems to implement stream joining yourself. In the final section, you will learn about tasks and alerts and how you can use Flux to create them with InfluxDB.
What you'll learn
  • How to use Flux window functions
  • How to create moving averages with Flux
  • How to create custom functions with Flux
  • How to join data streams together with Flux
  • How to create tasks and alerts using Flux
Recommended Resources
Riccardo Tommasini
Riccardo Tommasini is an Associate Professor (Maître des Confèrenecs) at the Institut National des Sciences Appliquées de Lyon or INSA Lyon, France. Prior to join INSA Lyon, Riccardo was Assistant Professor of Data management at the University of Tartu, Estonia. Riccardo did his PhD at the Department of Electronics and Information of the Politecnico di Milano with a thesis on “Velocity on the Web”. The thesis investigates the velocity aspects that concern the Web environment, together with other challenges such as variety and volume. His research interests span Stream Processing, Knowledge Graphs, Logics and Programming Languages. Riccardo’s tutorial activities comprise Stream Reasoning Tutorials at ISWC 2017, ICWE 2018, ESWC 2019, and TheWebConf 2019, and DEBS 2019, IEEE Big Data 2021.