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ThingWorx Analytics Training - Main Course Page

100% helpful (3/3)

Welcome to the ThingWorx Analytics Training Course!

 

Through these 11 modules, you will learn about:

  • ThingWorx Analytics, and how it integrates into the ThingWorx platform
  • Predictive analytics use cases, and what successful ones require
  • Basic data profiling methods, and how they help you build a meaningful predictive model
  • Data transformation & feature engineering, and how to build an analytics ready dataset
  • Descriptive analytics in the form of Signals and Profiles
  • Predictive machine learning models, and how to validate them
  • Obtaining and interpreting predictive & prescriptive scores
  • Time series data, and how it differs from other types of data sets 
  • Different forms of anomaly detection 

It is recommended that you have access to an environment running ThingWorx and ThingWorx Analytics version 9.2+. There are exercises in some of these modules that will help you better understand how to use the software. If you don't have access to an environment, you may simply follow along with the videos. 

 

This course doesn't cover the ThingWorx platform, and so you should have at least base-level experience with it before completing this course. Here is a great learning path to help you get up and running with ThingWorx.

 

NOTE: Complete the following modules in sequential order. The estimated time to complete this course is 10 hours.

 

Course Outline:

Module 1: ThingWorx Analytics Overview

Module 2: Use Case Discussion

Module 3: Data Profiling

Module 4: Data Transformation & Feature Engineering

Module 5: Descriptive Analytics

Module 6: Predictive Models & Model Validation

Module 7: Predictive & Prescriptive Scoring

Module 8: Time Series Modeling

Module 9: Anomaly Detection

Module 10: ThingWorx Foundation & Analytics Integration

Module 11: ThingWorx Analytics Mashup Exercise

 

Begin: Module 1 Part 1

Comments

This is great, thanks!

great info. thanks!

Not able to get the videos
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‎Jan 10, 2023 10:08 AM
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