CODeepLearning.AI · on Coursera
Structuring Machine Learning Projects
Intermediate English Professional CertificateFREE
What you'll learn
Set up train/dev/test splits that reflect your real goal
Diagnose whether bias or variance is limiting your model
Decide what to improve next using error analysis
Use a single evaluation metric to guide iteration
Apply transfer learning and multi-task learning appropriately
Avoid common traps that waste weeks of ML effort
This course includes
Yes
Certificate
Yes
Mobile access
English
Language
Comparison · LBS
Compare alternatives for Structuring Machine Learning Projects
Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
COCoursera—(0)
Structuring Machine Learning Projects
- Price
- FreeAudit free · Certificate available
- Duration
- —
- Level
- Intermediate
- Certificate
- Professional
COCoursera4.9(78,000)
Machine Learning Specialization
- Price
- FreeAudit free · Cert $49/mo
- Duration
- 94 hrs
- Level
- Intermediate
- Certificate
- Professional
COCoursera4.8(12,400)
AWS Certified AI Practitioner
- Price
- FreeAudit free · Cert $49/mo
- Duration
- 14 hrs
- Level
- Beginner
- Certificate
- Professional
COCoursera4.8(24,100)
Generative AI for Everyone
- Price
- FreeAudit free · Cert $49
- Duration
- 6 hrs
- Level
- Beginner
- Certificate
- Professional
Prices and ratings refreshed daily. We're not affiliated with any single provider.
Instructor
AN
Andrew Ng
Coursera instructor
— learners— courses — instructor rating
Andrew Ng — co-founder of Coursera and DeepLearning.AI — draws here on years of leading AI teams to teach the strategic instincts that separate productive ML work from spinning wheels. It's some of the most quietly valuable material in his specialization.
Requirements
- Basic machine-learning knowledge
- Familiarity with training models (e.g. from earlier specialization courses)
Who this course is for
- ML practitioners who can train models but struggle to improve them
- Engineers leading or scoping ML projects
- Learners in the Deep Learning Specialization
About this provider
CO
Coursera
University-backed online learning platform. 142M learners, 7,000+ courses from 325+ institutions.
4.6 trust score
Frequently asked questions
Yes — even outside the specialization, the strategy it teaches (where to focus, how to diagnose problems) is valuable to anyone working on real ML projects.
No — it's deliberately light on code and heavy on decision-making and strategy, which is unusual and part of why practitioners value it.
You can audit it free on Coursera. The certificate requires a subscription.
It helps to have basic ML knowledge, but the lessons here stand on their own well enough that experienced practitioners often take it standalone.
It's short — often completed in a few hours — but the ideas tend to pay off for years of project work.