Ementorhub

Managing Machine Learning Projects

This course is part of AI Product Management Specialization

Instructor: Jon Reifschneider

Skills you'll gain

Systems Architecture

Data Science

Applied Machine Learning

Machine Learning

MLOps (Machine Learning Operations)

Feature Engineering

Data Quality

Technology Solutions

Technical Management

Data Processing

Data Cleansing

Data Management

Software Development Life Cycle

Artificial Intelligence and Machine Learning (AI/ML)

Data Pipelines

Solution Design

Software Versioning

Data Collection

There are 5 modules in this course

At the conclusion of this course, you should be able to: 1) Identify opportunities to apply ML to solve problems for users 2) Apply the data science process to organize ML projects 3) Evaluate the key technology decisions to make in ML system design 4) Lead ML projects from ideation through production using best practices

Organizing ML Projects

Data Considerations

ML System Design & Technology Selection

Model Lifecycle Management

Explore more from Machine Learning

Planning a Machine Learning Project

Managing Machine Learning Projects with Google Cloud

Machine Learning Foundations for Product Managers

Structuring Machine Learning Projects