In the world of artificial intelligence, building a machine
learning model is only the first step. The real challenge lies
in deploying, monitoring, and maintaining it in a real-world
environment. Our AI/ML training is designed to bridge the gap
between data science and operations, empowering you to build
robust, scalable, and reliable ML pipelines.
We'll guide you through the principles and best practices of Machine Learning Operations, covering everything from version control for models to automated deployment and continuous monitoring.
Understand the complete workflow from model development to production.
Hands-on experience with industry-standard tools like TensorFlow Extended (TFX), Kubeflow, and MLflow.
Learn to automate your ML pipelines for seamless deployment.
Implement robust systems to detect model drift, data drift, and performance issues in real-time.
Ensure your models are transparent, reproducible, and compliant.