Introduction to Data Science for PI System Professionals

NEW - engage in Data Science initiatives with your PI System data

About this course

This lab is an introduction to Data Science concepts, for people who are familiar with using the basic PI tools. The scope of the lab is to introduce you to basic Data Science concepts and techniques, by going through the steps of a Data Science project example, from the formation of the Business Objective to Model Building and evaluation. The aim is to empower you in the process of engaging in Data Science initiatives. 

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

  • Publish PI datasets using PI Integrator for BA 
  • Explore data in Power BI, PI Vision, PI System Explorer 
  • Publish PI datasets to GCP end points and start analyzing/predicting the data using BigQuery ML 

Audience

This course is best suited for PI professionals familiar with basic PI tools that are trying to get started on data science projects. 

Level: Beginner

Study Time: 4 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 System and data flow (PI System Explorer, PI Vision) 
  • Basic directory navigation and management (Windows Explorer, creating and finding files) 
  • Basic Windows and Network security (why you log in, what is a domain, etc.) 
  • Familiarity with your real-time data sources (control systems, PLCs, OPC) 
  • A computer that can access our YouTube content, and pass our connection test
  • Browser with access to Google Cloud Platform (GCP) console (Chrome is highly recommended) 

Technical Prerequisites

  • Students will need to provide their own GCP account with at least free trial (billing) enabled. 
  • Students need to have the authorization to create a new project, or use an existing project in their GCP account. 
  • Have a GCP service account, or the ability to create a new one, with the following privilege at minimum (and create the JSON key).
  • BigQuery minimum permissions (this will be covered in the course): 
    • bigquery.datasets.create          
    • bigquery.datasets.get  
    • bigquery.datasets.update
    • bigquery.tables.create
    • bigquery.tables.list
    • bigquery.tables.delete
    • bigquery.tables.get       
    • bigquery.tables.update
  • BigQuery minimum roles:
    • roles/bigquery.dataEditor 

This Course Includes...

  • Videos, exercises and quizzes to help you learn the material
  • A Cloud Environment accessible for 30 days and configured to complete all the exercises in the course
  • A sharable certificate of completion

Further Information

  • 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 to Data Science, CRISM DM Methodology and the Business Objective
  • [POLL] Who's from what industry
  • [DISCUSSION] Introductions
  • Lesson 2 - Data Understanding
  • What data is available?
  • Data Understanding through PI Vision
  • Explore Generated Event Frames
  • Lesson 3 - Exploratory Data Analysis
  • Publish dataset using the PI Integrator for Business Analytics
  • Publishing to a CSV file
  • Publishing to a GCP BigQuery
  • Creating Reports for Data Exploration using Power BI (pt.1)
  • Creating Reports for Data Exploration using Power BI (pt.2)
  • Bivariate analysis in Power BI (pt.1)
  • Bivariate analysis in Power BI (pt.2)
  • Questions on this part of the course?
  • Lesson 4 - Modeling and Evaluation
  • Building a model in BigQuery ML
  • Loading the dataset
  • [TEXT] Filtering, Feature Engineering and Feature selection
  • Filtering Feature Engineering and Feature Selection
  • Introduction - How to choose the right model
  • How to choose the right model
  • Introduction - Results Evaluation
  • Results Evaluation
  • Questions on this part of the course?
  • Lesson 5 - Deployment
  • Bringing data back to PI
  • How did it go?
  • Course Evaluation
  • Final Exam
  • Final Exam

About this course

This lab is an introduction to Data Science concepts, for people who are familiar with using the basic PI tools. The scope of the lab is to introduce you to basic Data Science concepts and techniques, by going through the steps of a Data Science project example, from the formation of the Business Objective to Model Building and evaluation. The aim is to empower you in the process of engaging in Data Science initiatives. 

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

  • Publish PI datasets using PI Integrator for BA 
  • Explore data in Power BI, PI Vision, PI System Explorer 
  • Publish PI datasets to GCP end points and start analyzing/predicting the data using BigQuery ML 

Audience

This course is best suited for PI professionals familiar with basic PI tools that are trying to get started on data science projects. 

Level: Beginner

Study Time: 4 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 System and data flow (PI System Explorer, PI Vision) 
  • Basic directory navigation and management (Windows Explorer, creating and finding files) 
  • Basic Windows and Network security (why you log in, what is a domain, etc.) 
  • Familiarity with your real-time data sources (control systems, PLCs, OPC) 
  • A computer that can access our YouTube content, and pass our connection test
  • Browser with access to Google Cloud Platform (GCP) console (Chrome is highly recommended) 

Technical Prerequisites

  • Students will need to provide their own GCP account with at least free trial (billing) enabled. 
  • Students need to have the authorization to create a new project, or use an existing project in their GCP account. 
  • Have a GCP service account, or the ability to create a new one, with the following privilege at minimum (and create the JSON key).
  • BigQuery minimum permissions (this will be covered in the course): 
    • bigquery.datasets.create          
    • bigquery.datasets.get  
    • bigquery.datasets.update
    • bigquery.tables.create
    • bigquery.tables.list
    • bigquery.tables.delete
    • bigquery.tables.get       
    • bigquery.tables.update
  • BigQuery minimum roles:
    • roles/bigquery.dataEditor 

This Course Includes...

  • Videos, exercises and quizzes to help you learn the material
  • A Cloud Environment accessible for 30 days and configured to complete all the exercises in the course
  • A sharable certificate of completion

Further Information

  • 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 to Data Science, CRISM DM Methodology and the Business Objective
  • [POLL] Who's from what industry
  • [DISCUSSION] Introductions
  • Lesson 2 - Data Understanding
  • What data is available?
  • Data Understanding through PI Vision
  • Explore Generated Event Frames
  • Lesson 3 - Exploratory Data Analysis
  • Publish dataset using the PI Integrator for Business Analytics
  • Publishing to a CSV file
  • Publishing to a GCP BigQuery
  • Creating Reports for Data Exploration using Power BI (pt.1)
  • Creating Reports for Data Exploration using Power BI (pt.2)
  • Bivariate analysis in Power BI (pt.1)
  • Bivariate analysis in Power BI (pt.2)
  • Questions on this part of the course?
  • Lesson 4 - Modeling and Evaluation
  • Building a model in BigQuery ML
  • Loading the dataset
  • [TEXT] Filtering, Feature Engineering and Feature selection
  • Filtering Feature Engineering and Feature Selection
  • Introduction - How to choose the right model
  • How to choose the right model
  • Introduction - Results Evaluation
  • Results Evaluation
  • Questions on this part of the course?
  • Lesson 5 - Deployment
  • Bringing data back to PI
  • How did it go?
  • Course Evaluation
  • Final Exam
  • Final Exam