Enabling Enterprise-wide Data Science with OCS Dataviews

About this course

In this course, you will gain hands-on experience with a new OSIsoft software product, OSIsoft Cloud Services (OCS). OCS is a cloud-native platform built for historical, real-time and future/forecasted operational data. OCS complements existing on-premise PI systems and enables users to easily define, visualize, query and shape data sets required for data science.

By the end of the course, you will be able to...

Use the features and functionalities in OCS
Analyze & visualize data in OCS
Add metadata & create Data Views in OCS
Access OCS data in a Jupyter Notebook via Python
Filter & prepare data from OCS for machine learning
Use a machine learning model on a filtered OCS dataset
Retrieve weather data from a Weather API into the trained machine learning model
Send forecasted data back to OCS

Audience

This course is primarily suited for data scientists who are looking to extend operational data in their PI Systems for enterprise-wide machine learning applications.

Level: Intermediate

Study time: 16 hours

Course Access: Unlimited access. The only exception is the Training Cloud Environment for which you have 30 day access. After those 30 days you can purchase additional access with one of the two options below:

Prerequisites

Basic understanding of PI Server components, including PI Data Archive and PI Asset Framework
Basic understanding of Python, Jupyter Notebooks and machine learning
A computer that can access our YouTube content, and pass our connection test

This Course Includes...

Videos, discussion opportunities and quizzes to help you learn the material
A sharable certificate of completion

Further Information

This course assumes basic knowledge and understanding of wind turbines and their corresponding power curves. A brief introduction of wind turbine operation and relevant aspects of their power curves will be presented, but for additional information, please refer to the References section at the end.
This is a self-paced course. Any questions or assistance needed about the material can be asked in this course's space in the OSIsoft PI Square community
When you complete the examination at the end of the course, you will receive a certificate of completion which can be shared and directly posted on LinkedIn.
For more information about our Online Courses please visit our FAQ page

You can audit the full video lecture content right now on the OSIsoft Learning YouTube Channel

Curriculum

Getting Started
Key Course Information
Course Grading Scheme
How to Navigate This Course
Offline Course Videos for Blocked YouTube Users
Course Workbook
Course Presentation
Training Cloud Environment
Cloud Environments Introduction
Cloud Environments Instructions
Launch Cloud Environment
Lesson 1 - Introduction
Introduction
[POLL] Who's from what industry
[DISCUSSION] Introductions
Lesson 2 - Background Knowledge
Domain Knowledge – Machine Learning
Review the Wind Farm AF Model in PI System Explorer
Questions on this part of the course?
Lesson 3 - Introducing and Exploring OCS
Introducing OCS
Logging into & Navigating OCS
Questions on this part of the course?
Lesson 4 - Managing metadata in OCS
Metadata in OCS
Questions on this part of the course?
Lesson 5 - Creating Data Views in OCS
OCS Data Views
Questions on this part of the course?
Lesson 6 - OCS clients
OCS Clients
Questions on this part of the course?
Lesson 7 - Accessing Jupyter Notebook & Using API Console in OCS
How to access Jupyter Notebook
Introduction to OCS API Console and documentation
Prepare and check URL calls to access data in OCS
Getting data from data views
[PI SQUARE POLL] Python Proficiency Level
[PI SQUARE DISCUSSION] Jupyter Notebooks & Python
Questions on this part of the course?
Lesson 8 - Accessing OCS Data View and Preparing Dataset for Machine Learning
Introduction
Modify config.ini file and create new secret
Wind Turbine script walkthrough – part 1
Wind Turbine script walkthrough – part 2
Create new data view for turbine states
Wind Turbine script walkthrough – part 3 (Filters)
[PI SQUARE DISCUSSION] Python Plotting & Data Filtering
Questions on this part of the course?
Lesson 9 - Use Filtered Dataset to Train & Evaluate Machine Learning Model
Introduction
Prepare the training and testing data sets
Use the Decision Tree Regression ML model
Plot the results and save the ML model
Test the model and run sample prediction
[PI SQUARE DISCUSSION] Machine Learning Models
Questions on this part of the course?
Lesson 10 - Getting Forecast Weather Data into ML Model
Introduction
Retrieve weather forecast
Store JSON response in data frame
Use the ML model to predict Active Power
[PI SQUARE DISCUSSION] Retrieving Live & Forecasted Weather Data
Questions on this part of the course?
Lesson 11 - Sending Data Back to OCS
Introduction
OMF overview
OMF and connections
Send data to OCS (create SDS Type)
Send data to OCS (create Stream)
Send data to Stream and trend
Lab summary
[PI SQUARE DISCUSSION] Sending Data Back to OCS
[PAGE] Useful Links
Questions on this part of the course?
Course Evaluation
Final Exam
Final Exam

About this course