Automate ML Pipelines for Peak Performance
By Coursera
on Coursera
· Data Science
About This Course
This course teaches you how to build a fully automated machine learning pipeline using scikit-learn. You will learn to scale numeric features, encode categorical variables, train a logistic model, and optimize it using GridSearchCV. The course then guides you in packaging the workflow as a reusable module that fits real-world ML engineering and MLOps practices. Through concise videos, structured readings, two 15-minute Coach interactions, a combined 25-minute hands-on activity, and a 45-minute ungraded lab, you will practice constructing and refining an end-to-end pipeline. By the end, you will have a polished, automated workflow you can reuse, adapt, and integrate into your ML projects or production systems.
Instructor
ansrsource instructors
Frequently Asked Questions
How much does Automate ML Pipelines for Peak Performance cost?
Visit the Automate ML Pipelines for Peak Performance course page for current pricing and available discounts.
Who teaches Automate ML Pipelines for Peak Performance?
Automate ML Pipelines for Peak Performance is taught by ansrsource instructors, Coursera.
What skill level is Automate ML Pipelines for Peak Performance for?
This course is designed for all levels learners.