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Machine Learning Operations (MLOps) for Generative AI Training

Live Online & Classroom Enterprise Training

Learn how to operationalize Generative AI models using MLOps practices including model deployment, monitoring, automation, governance, and scaling in production environments.

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What is Machine Learning Operations (MLOps) for Generative AI Course about?

This course provides a comprehensive understanding of how MLOps principles are applied to Generative AI systems. It covers model lifecycle management, CI/CD for ML pipelines, data versioning, monitoring model drift, security, and responsible AI practices. Learners will gain hands-on exposure to deploying and managing large language models (LLMs) and generative models in real-world production environments using modern MLOps tools and cloud platforms.

What are the objectives of Machine Learning Operations (MLOps) for Generative AI Course ?

  • Understand MLOps fundamentals for Generative AI workflows
  • Build automated CI/CD pipelines for GenAI model deployment
  • Implement monitoring, logging, and model performance tracking
  • Manage data, model versioning, and experiment tracking
  • Apply governance, security, and responsible AI practices

Who is Machine Learning Operations (MLOps) for Generative AI Course for?

  • Machine Learning Engineers
  • Data Scientists working with Generative AI
  • AI/ML Architects
  • DevOps Engineers moving into MLOps
  • Cloud Engineers managing AI workloads

What are the prerequisites for Machine Learning Operations (MLOps) for Generative AI Course?

Prerequisites:

  • Basic understanding of Machine Learning concepts
  • Familiarity with Python programming
  • Knowledge of cloud platforms (AWS, Azure, or GCP basics)
  • Understanding of Git and CI/CD concepts
  • Basic knowledge of APIs and containers (Docker basics)


Learning Path:

  • Foundations of MLOps and Generative AI
  • Data Engineering and Model Training Pipelines
  • Model Deployment Strategies for GenAI
  • Monitoring, Observability, and Model Governance
  • Scaling and Optimizing Generative AI Systems


Related Courses:

  • Introduction to Generative AI
  • Advanced Machine Learning Engineering
  • Kubernetes for Machine Learning Workloads
  • Cloud AI/ML Services Implementation

Available Training Modes

Live Online Training

1 Days

Course Outline Expand All

Expand All

  • Understanding the unique challenges of deploying and managing Generative AI models
  • Overview of MLOps principles and their application to Generative AI
  • Exploring how Vertex AI supports MLOps processes
  • Tools and features in Vertex AI that streamline Generative AI workflows
  • Best practices for managing the lifecycle of Generative AI models
  • Techniques for monitoring, updating, and scaling AI models in production

Who is the instructor for this training?

The trainer for this Machine Learning Operations (MLOps) for Generative AI Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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