IL - AI – 101 Artificial Intelligence in Process Optimization - Instructor - Led
This course provides participants with the background knowledge and basic skills needed to use machine learning techniques to transform process data to real insights that drive process control decisions. Through a combination of presented materials, Python code exercises, and data engineering & modeling challenges, participants will gain the ability to engineer and model any process data using Python code and advanced AI techniques.
Description
Duration: 12 hours (in-person)
*in-person at a TriNova facility includes breakfast & lunch
Dates & Times: By appointment
Location: TriNova location
Instructor: Thomas Casey, Ph.D.
Basic Level
AI – 101
Day 1:
Section 1 – Python Basics
Introduction to Python coding including variables, loops, functions, classes, and more
Apply your Python skills by starting your own code library
Section 2 – Basic Data Engineering
Importing and cleaning process data
Common metrics & visualization techniques
Day 2:
Section 3 – Basic Data Science
Statistical analyses of process data
Introduction to Machine Learning
Section 4 – Basics of Process Data Modeling
Anomaly detection & soft sensors
Control models & Reinforcement Learning
Prerequisites
Prerequisites: Participants should be familiar with handling process data and common numerical techniques. Python experience is not required.