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SaaS, Apps & Coding

Learn to Build Machine Learning Systems That Don't Suck (2019)

Learn to Build Machine Learning Systems That Don't Suck is a live, hands-on ml.school program on building production-ready AI and ML systems.

Learn to Build Machine Learning Systems That Don't Suck (2019) cover image

About Learn to Build Machine Learning Systems That Don't Suck (2019)

Building AI/ML Systems That Don't Suck is a live, interactive program from ml.school for developers who want to solve real-world problems with machine learning. Instead of focusing on theory, it concentrates on engineering skills for taking a model from idea to a system that runs reliably in production, and the listing refers to the 2019 version.

The sessions begin with how to start almost any project, including an eight-question checklist, then move to choosing and evaluating a working model and getting models ready for production. The page also mentions an end-to-end system built from scratch, a private community and lifetime access to future cohorts. Check the official page for the full session list.

What You'll Learn

  • Starting machine learning projects the right way
  • Choosing and evaluating a working model
  • Getting models ready for production
  • Monitoring and maintaining ML systems

Who Is This Course For?

  • Developers moving models to production
  • Data scientists learning MLOps
  • ML engineers building end-to-end systems
  • Software engineers adding ML skills
  • Teams wanting reliable ML pipelines

Suited to developers who want to move from experimenting with models to engineering production-ready machine learning systems.

AdvancedIt targets developers solving real-world production problems, so it expects programming and ML familiarity. It is not an intro to machine learning.

Why Choose Learn to Build Machine Learning Systems That Don't Suck (2019)?

The ml.school program is described as live, hands-on training for building production-ready machine learning systems, with sessions on starting projects, choosing and evaluating models and getting them production-ready. The page mentions an end-to-end system built from scratch and lifetime access to future cohorts and a community.

Course Highlights

  • Live interactive sessions
  • End-to-end system walkthrough
  • Future cohorts access
  • Private community

Before You Buy

  • Read the full curriculum on the official page and make sure it matches your level.
  • Check what's included: updates, community, coaching calls or templates.
  • Look for the refund policy and guarantee terms.
  • Compare it with the similar SaaS, Apps & Coding courses below.

Frequently Asked Questions

Is Learn to Build Machine Learning Systems That Don't Suck (2019) good for beginners?

No, it is aimed at people with a technical background. It targets developers solving real-world production problems, so it expects programming and ML familiarity. It is not an intro to machine learning.

What does Learn to Build Machine Learning Systems That Don't Suck (2019) cover?

The official page lists sessions on starting any project, choosing and evaluating a working model, and preparing systems for production.

What is the focus of the program?

The official page says it teaches production-ready AI and ML systems from the ground up for developers.

Where can I buy Learn to Build Machine Learning Systems That Don't Suck (2019)?

The course is sold by the creator on ml.school; check the official page for current details.

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