MLOps: Foundations

Teacher

Marouene Oueslati

Categories

MLOps

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Machine Learning Operations (MLOps) refers to the tools, techniques and practical experiences required to train your machine learning models and deploy and monitor them in production. After we have trained our machine learning model, the next big task is to deploy the model to production and scale it so that more users can use it. In this course, you will learn how to use various tools and methodologies to do all this effectively.

While knowing machine learning and deep learning concepts is essential, but for building a successful career in Artiﬁcial Intelligence, you need to have good experience with production engineering capabilities. This course deep-dives into machine learning and deep learning algorithms along with building expertise in DevOps technologies.

By the end of this program, you will be ready to:

Design a machine learning system end-to-end starting from project scoping, data needs, modeling and deployment.
Build pipelines for optimizing the model training process.
Apply various machine learning and deep learning algorithms to solve your business problems.
Use Spark MLlib and Spark for distributed model training.
Deploy your machine learning models to production using CI/CD pipelines.
Monitor and visualize the performance of your system.
Gain practical knowledge in TensorFlow, Keras, Linux, Git, Python, Docker, Kubernetes, Ansible, Terraform, Graffana, Prometheus and Jenkins.