DataOps & MLOps for Scalable AI Pipelines

  • Last Updated: May 19, 2025
  • english,arabic

Overview

The DataOps & MLOps for Scalable AI Pipelines program is designed for data engineers, machine learning engineers, and AI practitioners who want to streamline the development, deployment, and monitoring of AI and data workflows. This program covers best practices, tools, and automation techniques to enhance data pipeline efficiency and machine learning model lifecycle management. Participants will gain hands-on experience with CI/CD for AI models, automated data pipelines, monitoring, and governance using Kubernetes, Apache Airflow, MLflow, Kubeflow, and cloud platforms (AWS, GCP, Azure).

  • Automate data engineering workflows with DataOps.
  • Implement MLOps practices for scalable AI model deployment.

  • Introduction to DataOps & MLOps
  • DataOps Fundamentals for AI Pipelines
  • Feature Engineering & Data Versioning
  • Machine Learning Model Deployment & CI/CD
  • Kubernetes & Cloud-Native MLOps
  • Monitoring & Observability in AI Pipelines
  • Governance, Security & Compliance in MLOps
  • Scalable & Cost-Optimized AI Pipelines
  • Capstone Project – End-to-End MLOps Pipeline

  • Update:May 19, 2025
  • Lectures16
  • Skill LevelAll Levels
  • LanguageEnglish
  • Course Duration: 40h
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DataOps & MLOps for Scalable AI Pipelines
AED90.00 AED100.00
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