By DataCamp
Master MLOps fundamentals, model deployment, and production ML systems to become a junior machine learning engineer
Solid beginner-to-intermediate MLOps foundation with hands-on projects, but you'll need additional real-world experience for job readiness.
Covers essential MLOps topics like Docker, CI/CD, monitoring. Some reviewers find it basic for real-world production needs.
DataCamp's interactive format with short videos plus hands-on exercises is highly effective for practical learning.
Excellent browser-based environment, mobile app support, and cloud IDE eliminate setup barriers for learners.
At ~$30/month (often 50% off) for 44 hours of structured content, it's cost-effective compared to bootcamps.
Good foundation for MLOps concepts, but graduates need additional projects and real-world experience for job readiness.
You have ML fundamentals but need MLOps and deployment skills
Perfect for data scientists wanting to transition into ML engineering roles with structured, practical learning.
You already work with production ML systems daily
The content may be too basic if you're already deploying models and managing ML infrastructure professionally.
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