- Command-Line Interface
- Artificial Intelligence and Machine Learning (AI/ML)
- Serverless Computing
- PyTorch (Machine Learning Library)
- GitHub
- Cloud Solutions
- CI/CD
- Machine Learning
- Containerization
- Tensorflow
- Responsible AI
- Web Frameworks
DevOps, DataOps, MLOps
Completed by Raigon Padikkala Rappai
May 3, 2024
44 hours (approximately)
Raigon Padikkala Rappai's account is verified. Coursera certifies their successful completion of DevOps, DataOps, MLOps
What you will learn
Build operations pipelines using DevOps, DataOps, and MLOps
Explain the principles and practices of MLOps (i.e., data management, model training and development, continuous integration and delivery, etc.)
Build and deploy machine learning models in a production environment using MLOps tools and platforms.