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Managing Pipelines with Metaflow

Learn the best practices of building Data and ML pipelines!

Duration

2 days (8 hours per day)

Level

Basic Level

Design and Tailor this course

As per your team needs

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This course aims to provide comprehensive training on Metaflow, a powerful tool for building and managing ml & data pipelines. Participants will gain a deep understanding of Metaflow’s architecture, features, and applications across industries. Through hands-on demonstrations, they will learn to install, configure, and integrate Metaflow in various environments. The course covers essential skills in creating and managing flows, implementing monitoring and logging strategies, and scaling pipelines efficiently.

Participants will master best practices for design, resource management, and cost optimization in cloud environments. By the end of the course, attendees will be equipped to effectively implement and manage Metaflow-based data pipelines in their professional projects.



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  • Data Engineers
  • Data Scientists
  • Machine Learning Engineers
  • IT Professionals involved in data management and workflow orchestration
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  • Overview of Metaflow and its architecture
  • Key features and benefits of using Metaflow for data pipelines
  • Use cases for Metaflow in various industries
  • System requirements and prerequisites
  • Installation steps for different environments (local, cloud)
  • Configuration settings for Metaflow
  • Integrating Metaflow with other tools and services
  • Hands-on Demo:
    • Installing Metaflow on a local machine
    • Configuring Metaflow for a specific environment
  • Understanding Metaflow flows and steps
  • Creating and managing flows using Metaflow
  • Using the Metaflow CLI for pipeline operations
  • Best practices for designing and organizing flows
  • Hands-on Demo:
    • Creating and running a simple flow
    • Managing flow versions and dependencies
  • Importance of monitoring and logging in data and ml pipelines
  • Tools and techniques for monitoring Metaflow pipelines
  • Setting up logging for flows and steps
  • Analyzing logs and troubleshooting issues
  • Hands-on Demo:
    • Setting up monitoring for a Metaflow pipeline
    • Implementing logging and analyzing log data
  • Understanding resource management in Metaflow
  • Techniques for scaling Metaflow pipelines
  • Managing compute and storage resources efficiently
  • Best practices for cost optimization in cloud environments
  • Hands-on Demo:
    • Scaling a Metaflow pipeline to handle large datasets
    • Managing resources and optimizing costs in the cloud
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  • Basic understanding of data and ml pipelines 
  • Basic understanding of workflow orchestration
  • Familiarity with Python programming
  • Basic knowledge of cloud computing and resource management

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