Master Ml pipelines Training Courses

Training Course on Cloud MLOps on AWS (SageMaker Advanced): Deep Dive into AWS Services for MLOps provides a comprehensive, hands-on deep dive into Cloud MLOps principles and practices, specifically leveraging advanced AWS services, with a strong focus on Amazon SageMaker

Training Course on Cloud MLOps on Azure (Azure ML Advanced): Deep dive into Azure services for MLOps. is meticulously designed to equip professionals with the cutting-edge skills and best practices required to streamline the entire Machine Learning Lifecycle on Microsoft Azure.

Training Course on Cloud MLOps on GCP (Vertex AI Advanced): Deep Dive into GCP Services for MLOps provides a deep dive into Cloud MLOps on Google Cloud Platform (GCP), specifically leveraging Vertex AI Advanced capabilities. Participants will gain hands-on expertise in building, deploying, monitoring, and managing robust Machine Learning (ML) pipelines in a production environment.

Training Course on Data Lineage & Provenance for Trustworthy AI delves into the critical disciplines of Data Lineage and Data Provenance, equipping professionals with the essential knowledge and practical skills to meticulously track data origins, transformations, and usage within complex AI pipelines.

Training Course on Data Versioning & Experiment Tracking for ML: Tools like DVC, MLflow for Reproducible Research delves into the critical practices of data versioning and experiment tracking, empowering data scientists, ML engineers, and researchers to effectively manage their ML workflows.

Training Course on Feature Engineering & Selection (Advanced) goes beyond foundational concepts, exploring advanced methodologies for data preprocessing, feature creation, and dimensionality reduction.

Training Course on Feature Store Design & Implementation: Centralizing and Serving Features for ML Models outlines a comprehensive training course on Feature Store Design & Implementation, a critical component of modern MLOps.