MLOps Course

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Learn how to combine machine learning with software engineering to design, develop, deploy and iterate on production ML applications.

Goku Mohandas

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1. 🎨 Design

2. 🔢 Data

3. 🤖 Model

4. 💻 Develop

5. 📦 Utilities

6. 🧪 Test

7. ♻️ Reproducibility

Versioning

8. 🚀 Production

Live cohort

Sign up for our upcoming live cohort, where we'll provide live lessons + QA, compute (GPUs) and community to learn everything in one day.

While the specific task in this course involves fine-tuning an LLM for a supervised task, everything we learn easily extends to all applications (NLP, CV, time-series, etc.), models (regression → LLMs), data modalities (tabular, text, etc.), cloud platforms (AWS, GCP) and scale (local laptop → distributed cluster).

Upcoming live cohorts

Sign up for our upcoming live cohort, where we'll provide live lessons + QA, compute (GPUs) and community to learn everything in one day.

To cite this content, please use:

@article{madewithml,
    author       = {Goku Mohandas},
    title        = { MLOps Course - Made With ML },
    howpublished = {\url{https://madewithml.com/}},
    year         = {2023}
}