Current
Intermediate
The Machine Learning Lifecycle: From Data Ingestion to Responsible Deployment
LinkedIn Learning · LinkedIn Learning · Updated March 2026
Platform rating
4.6/5
AI Tutor Rating
8.6/10
Duration
3-4 hours video
Classes
12
Learn the complete machine learning lifecycle from initial data ingestion through to responsible deployment in production. This course covers best practices for building, validating, and deploying ML models while considering ethical implications and responsible AI practices.
What you'll get
Understand the complete ML lifecycle from data to deployment
Implement responsible AI practices in model development
Deploy machine learning models effectively in production
Address ethical considerations in ML projects
Fit
Best for
Developers
AI Engineers
Data Scientists
Technical Builders
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Basic understanding of machine learning concepts
Pricing
Subscription
Certification
Certificate
Growth Leverage: Completing this course opens pathways to roles such as Machine Learning Engineer, Data Scientist, or AI Ethics Consultant. Additionally, it positions you for certifications like the Certified Data Professional (CDP) or Microsoft Certified: Azure Data Scientist Associate, enhancing your career prospects in AI-driven industries.
Skills Value: The skills gained allow you to effectively implement ethical AI practices and robust deployment strategies, addressing critical issues like bias in models. With demand for responsible AI solutions rising, professionals in these roles can command salaries 10-20% higher than their peers, reflecting market value.
Machine Learning
ML Lifecycle
Responsible AI
Data Science
Deployment