Artificial Intelligence
Intermediate 10 weeks
Machine Learning with Python
Learn how to build, evaluate and deploy machine learning models with Python using real-world datasets and practical business problems.
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Artificial Intelligence
AI/ML Engineering
Engineer machine-learning systems from data preparation and model evaluation through reproducible serving and operational monitoring.
Register for This CourseLevel
Advanced
Duration
12 weeks
Delivery
Physical & Live Online
Category
Artificial Intelligence
Practice the engineering lifecycle for machine-learning systems, including reproducible experiments, model serving, evaluation, and monitoring.
Course overview
An applied ML systems course emphasizing the engineering lifecycle around model development: experiment reproducibility, data and model validation, deployment interfaces, monitoring, and maintenance. It complements the broader AI Engineering certificate with a focused implementation track.
Who it's for: Python developers and data practitioners with foundational machine-learning knowledge who want to engineer maintainable model services.
What you will learn
- Build reproducible training and evaluation workflows
- Package models behind versioned prediction interfaces
- Track model quality and data changes after deployment
- Document and maintain an end-to-end ML service
Curriculum
Tools you'll use
Pythonscikit-learnFastAPIDockerGit
Projects you'll build
- Reproducible ML pipeline
- Versioned prediction API
- Monitored model service
Prerequisites
- • Python programming experience
- • Foundational machine-learning concepts
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