How to Learn MLOps in 2024 [Courses, Books, and Other Resources]
Blog post from Neptune.ai
With the growing importance of Machine Learning Operations (MLOps) due to advancements in machine learning and the rise of Large Language Models (LLMs), this article provides a comprehensive guide to learning MLOps in 2024. MLOps, which combines data science, DevOps, and software engineering, is critical for deploying and managing ML models at scale. The piece offers a detailed learning roadmap, highlighting resources like courses, books, YouTube channels, podcasts, and community forums. It emphasizes the significance of understanding different aspects of MLOps, from model deployment and monitoring to data management and system design. The article recommends resources tailored to various backgrounds, such as data scientists, ML engineers, and software developers, and discusses the importance of engaging with MLOps communities and attending conferences to stay updated with industry trends.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 11 | 3,889 | 441 | 129 | +7% |
| Kubernetes | 2 | 1,245 | 176 | 79 | -2% |
| Real-time | 2 | 3,932 | 887 | 192 | +47% |
| AI Coding Assistant | 1 | 677 | 96 | 46 | +48% |
| AI Guardrails | 1 | 126 | 55 | 33 | -17% |
| Reinforcement learning | 1 | No monthly metrics for this publish month. | |||
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