> For the complete documentation index, see [llms.txt](https://www.mlcompendium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.mlcompendium.com/ai-engineering/mlops-course.md). # MLOps Course Reading about MLOps is not the same as practicing it. The shelf here is two Weights & Biases courses, first for model development and then for CI/CD. The same notes are in [Continuous Integration](/ai-engineering/full-stack-and-ops-1/continuous-integration.md). ## Weights & Biases Both courses come from the same vendor, so they follow one workflow from design to deployment. The same notes are in [Experiment platforms](/ai-engineering/experiment-management.md#experiment-platforms). The first course is about the model itself: [Effective MLOps for data scientists](https://www.wandb.courses/courses/effective-mlops-model-development) is tailored for effective model development, streamlining the ML workflow from design to deployment with W\&B. Once a model can be developed that way, the second course automates its delivery: [CI/CD using GitOps and W\&B](https://www.wandb.courses/courses/ci-cd-for-machine-learning) is the free CI/CD course on best practices for continuous integration and deployment of ML workflows. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://www.mlcompendium.com/ai-engineering/mlops-course.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.