Made With ML

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Made With ML is an educational platform that teaches how to responsibly design, develop, deploy, and iterate on production machine learning applications. It offers courses and resources for ML practitioners.

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At a glance

Pricing

Likely Not Free

Free tier

API

Skill level

Technical

About

What is Made With ML?

Made With ML by Anyscale provides comprehensive courses and resources for individuals looking to master the entire lifecycle of production machine learning applications. The platform covers essential topics from design and data handling to model training, deployment, and iteration. It emphasizes best practices in software engineering for ML, scalability, MLOps integration, and CI/CD workflows. The content is designed for a diverse audience, including software engineers, data scientists, college graduates, and product/leadership roles, aiming to bridge the gap between academic knowledge and industry expectations. The curriculum focuses on first principles, practical skills, and scaling ML workloads in Python, ensuring learners can confidently go from development to production.

Best used for

Ideal for developers, data scientists, and product/leadership roles who need to learn how to design, develop, and deploy production-grade machine learning applications. Especially valuable for those looking to implement MLOps best practices and scale ML workloads effectively.

Common actions

learn machine learning

develop ML applications

deploy ML models

understand MLOps

scale ML workloads

Capabilities

Key features

ML design principles
Data preparation techniques
Model training/tuning/serving
CI/CD workflows
MLOps integration
Python ML scalability

Target Audience

professorteachercoach

Integrations

Not yet documented

Pricing & Plans

Likely Not Free

Not publicly disclosed. Check madewithml.com for current pricing.

FAQs

What are the prerequisites for taking the Made With ML course?

To get the most out of the course, you should have a basic understanding of Python programming, including NumPy and Pandas, and foundational knowledge of machine learning concepts like logistic regression or PyTorch.

What is the time commitment required for the Made With ML course?

You can progress through the lessons at your own pace. Alternatively, you can sign up for an upcoming live cohort, which offers live lessons, Q&A sessions, compute resources (GPUs), and community interaction, all completed in one day.

What kind of support is available after completing the course?

After finishing the course, you gain access to a private community. This allows you to connect with alumni, meet future cohort members, ask questions about topics, and receive feedback on your work as new tools and practices emerge.

Does the course cover specific ML domains or models?

While the specific task in the course involves fine-tuning an LLM, the principles and practices taught are broadly applicable. They extend to various applications (NLP, CV, time-series), models (regression to LLMs), data modalities, cloud platforms (AWS, GCP), and scales.

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