{"id":15036699,"url":"https://github.com/datatalksclub/mlops-zoomcamp","last_synced_at":"2025-05-12T13:07:13.119Z","repository":{"id":36961573,"uuid":"419662458","full_name":"DataTalksClub/mlops-zoomcamp","owner":"DataTalksClub","description":"Free MLOps course from DataTalks.Club","archived":false,"fork":false,"pushed_at":"2025-05-09T09:30:41.000Z","size":11709,"stargazers_count":12445,"open_issues_count":9,"forks_count":2418,"subscribers_count":201,"default_branch":"main","last_synced_at":"2025-05-12T13:06:50.833Z","etag":null,"topics":["machine-learning","mlops","model-deployment","model-monitoring","workflow-orchestration"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DataTalksClub.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2021-10-21T09:35:28.000Z","updated_at":"2025-05-12T13:03:08.000Z","dependencies_parsed_at":"2023-02-12T01:01:33.197Z","dependency_job_id":"c7df0c9d-de09-4b3a-a99c-9106ac8d72d4","html_url":"https://github.com/DataTalksClub/mlops-zoomcamp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DataTalksClub%2Fmlops-zoomcamp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DataTalksClub%2Fmlops-zoomcamp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DataTalksClub%2Fmlops-zoomcamp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DataTalksClub%2Fmlops-zoomcamp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DataTalksClub","download_url":"https://codeload.github.com/DataTalksClub/mlops-zoomcamp/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253745152,"owners_count":21957317,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning","mlops","model-deployment","model-monitoring","workflow-orchestration"],"created_at":"2024-09-24T20:31:58.639Z","updated_at":"2025-05-12T13:07:13.081Z","avatar_url":"https://github.com/DataTalksClub.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cimg width=\"80%\" src=\"images/banner-2025.jpg\" alt=\"MLOps Zoomcamp\"\u003e\n\u003c/p\u003e\n\n\u003ch1 align=\"center\"\u003e\n    \u003cstrong\u003eMLOps Zoomcamp: A Free 9-Week Course on Productionizing ML Services\u003c/strong\u003e\n\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\nMLOps (machine learning operations) is a must-know skill for many data professionals. Master the fundamentals of MLOps, from training and experimentation to deployment and monitoring.\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://airtable.com/shrCb8y6eTbPKwSTL\"\u003e\u003cimg src=\"https://user-images.githubusercontent.com/875246/185755203-17945fd1-6b64-46f2-8377-1011dcb1a444.png\" height=\"50\" /\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://datatalks.club/slack.html\"\u003eJoin Slack\u003c/a\u003e •\n\u003ca href=\"https://app.slack.com/client/T01ATQK62F8/C01FABYF2RG\"\u003e#course-mlops-zoomcamp Channel\u003c/a\u003e •\n\u003ca href=\"https://t.me/dtc_courses\"\u003eTelegram Announcements\u003c/a\u003e •\n\u003ca href=\"https://www.youtube.com/playlist?list=PL3MmuxUbc_hIUISrluw_A7wDSmfOhErJK\"\u003eCourse Playlist\u003c/a\u003e •\n\u003ca href=\"https://docs.google.com/document/d/12TlBfhIiKtyBv8RnsoJR6F72bkPDGEvPOItJIxaEzE0\"\u003eFAQ\u003c/a\u003e •\n\u003ca href=\"https://ctt.ac/fH67W\"\u003eTweet about the Course\u003c/a\u003e\n\u003c/p\u003e\n\n## How to Take MLOps Zoomcamp\n\n### 2025 Cohort\n- **Start Date**: May 5, 2025\n- **Register Here**: [Sign up](https://airtable.com/shrCb8y6eTbPKwSTL)\n- **Stay Updated**: Subscribe to our [Google Calendar](https://calendar.google.com/calendar/?cid=M3Jzbmg0ZDA2aHVsY2M1ZjcyNDJtODNyMTRAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ) (Desktop only)\n\n### Self-Paced Learning\nAll course materials are freely available for independent study. Follow these steps:\n1. Watch the course videos.\n2. Join the [Slack community](https://datatalks.club/slack.html).\n3. Refer to the [FAQ document](https://docs.google.com/document/d/12TlBfhIiKtyBv8RnsoJR6F72bkPDGEvPOItJIxaEzE0/edit) for guidance.\n\n## Syllabus\nThe course consists of structured modules, hands-on workshops, and a final project to reinforce your learning. Each module introduces core MLOps concepts and tools.\n\n### Prerequisites\nTo get the most out of this course, you should have prior experience with:\n- Python\n- Docker\n- Command line basics\n- Machine learning (e.g., through [ML Zoomcamp](https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp))\n- 1+ year of programming experience\n\n## Modules\n\n### [Module 1: Introduction](01-intro)\n- What is MLOps?\n- MLOps maturity model\n- NY Taxi dataset (our running example)\n- Why MLOps is essential\n- Course structure \u0026 environment setup\n- Homework\n\n### [Module 2: Experiment Tracking \u0026 Model Management](02-experiment-tracking)\n- Introduction to experiment tracking\n- MLflow basics\n- Model saving and loading\n- Model registry\n- Hands-on MLflow exercises\n- Homework\n\n### [Module 3: Orchestration \u0026 ML Pipelines](03-orchestration)\n\n- Workflow orchestration\n- Homework\n\n### [Module 4: Model Deployment](04-deployment)\n- Deployment strategies: online (web, streaming) vs. offline (batch)\n- Deploying with Flask (web service)\n- Streaming deployment with AWS Kinesis \u0026 Lambda\n- Batch scoring for offline processing\n- Homework\n\n### [Module 5: Model Monitoring](05-monitoring)\n- Monitoring ML-based services\n- Web service monitoring with Prometheus, Evidently, and Grafana\n- Batch job monitoring with Prefect, MongoDB, and Evidently\n- Homework\n\n### [Module 6: Best Practices](06-best-practices)\n- Unit and integration testing\n- Linting, formatting, and pre-commit hooks\n- CI/CD with GitHub Actions\n- Infrastructure as Code (Terraform)\n- Homework\n\n### [Final Project](07-project/)\n- End-to-end project integrating all course concepts\n\n## Community \u0026 Support\n\n### Getting Help on Slack\n\nJoin the [`#course-mlops-zoomcamp`](https://app.slack.com/client/T01ATQK62F8/C02R98X7DS9) channel on [DataTalks.Club Slack](https://datatalks.club/slack.html) for discussions, troubleshooting, and networking.\n\nTo keep discussions organized:\n- Follow [our guidelines](asking-questions.md) when posting questions.\n- Review the [community guidelines](https://datatalks.club/slack/guidelines.html).\n\n## Instructors\n\n- [Cristian Martinez](https://www.linkedin.com/in/cristian-javier-martinez-09bb7031/)\n- [Alexey Grigorev](https://www.linkedin.com/in/agrigorev/)\n- [Emeli Dral](https://www.linkedin.com/in/emelidral/)\n\n\n## Sponsors \u0026 Supporters\n\nInterested in supporting our community? Reach out to [alexey@datatalks.club](mailto:alexey@datatalks.club).\n\n## About DataTalks.Club\n\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"40%\" src=\"https://github.com/user-attachments/assets/1243a44a-84c8-458d-9439-aaf6f3a32d89\" alt=\"DataTalks.Club\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://datatalks.club/\"\u003eDataTalks.Club\u003c/a\u003e is a global online community of data enthusiasts. It's a place to discuss data, learn, share knowledge, ask and answer questions, and support each other.\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n\u003ca href=\"https://datatalks.club/\"\u003eWebsite\u003c/a\u003e •\n\u003ca href=\"https://datatalks.club/slack.html\"\u003eJoin Slack Community\u003c/a\u003e •\n\u003ca href=\"https://us19.campaign-archive.com/home/?u=0d7822ab98152f5afc118c176\u0026id=97178021aa\"\u003eNewsletter\u003c/a\u003e •\n\u003ca href=\"http://lu.ma/dtc-events\"\u003eUpcoming Events\u003c/a\u003e •\n\u003ca href=\"https://calendar.google.com/calendar/?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ\"\u003eGoogle Calendar\u003c/a\u003e •\n\u003ca href=\"https://www.youtube.com/@DataTalksClub/featured\"\u003eYouTube\u003c/a\u003e •\n\u003ca href=\"https://github.com/DataTalksClub\"\u003eGitHub\u003c/a\u003e •\n\u003ca href=\"https://www.linkedin.com/company/datatalks-club/\"\u003eLinkedIn\u003c/a\u003e •\n\u003ca href=\"https://twitter.com/DataTalksClub\"\u003eTwitter\u003c/a\u003e\n\u003c/p\u003e\n\nAll the activity at DataTalks.Club mainly happens on [Slack](https://datatalks.club/slack.html). We post updates there and discuss different aspects of data, career questions, and more.\n\nAt DataTalksClub, we organize online events, community activities, and free courses. You can learn more about what we do at [DataTalksClub Community Navigation](https://www.notion.so/DataTalksClub-Community-Navigation-bf070ad27ba44bf6bbc9222082f0e5a8?pvs=21).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatatalksclub%2Fmlops-zoomcamp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatatalksclub%2Fmlops-zoomcamp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatatalksclub%2Fmlops-zoomcamp/lists"}