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Overview

This certification & training course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models
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What You'll Learn

  • Identify and use core technologies required to support effective MLOps.
  • Configure and provision Google Cloud architectures for reliable and effective MLOps environments.
  • Implement reliable and repeatable training and inference workflows.
  • Adopt the best CI/CD practices in the context of ML systems.
  • Operate deployed machine learning models effectively and efficiently. 
  • Identify and use core technologies required to support effective MLOps.

Who Should Attend

  • Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact.
  • Software Engineers looking to develop Machine Learning Engineering skills. ?ML Engineers who want to adopt Google Cloud.
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Prerequisites

Completed Machine Learning with Google Cloud or have equivalent experience

Learning Journey

Want to boost your career in Google Cloud? Click on the roles below to see the learning pathways, specially designed to give you the skills to succeed.

The course includes presentations, demonstrations, and hands-on labs.

Module 1: Why and When do we need MLOps
  •  Discuss Data Scientists' pain points.
  •  Identify ML Engineering characteristics and challenges.
  •  Define how Google Cloud can help with MLOps.
  •  Recognize how MLOps differs from manual ML management.
  •  Compare and contrast DevOps vs MLOps.
Module 2: Understanding the Main Kubernetes Components (Optional)
  •  Define what is a Docker container.
  •  Create Docker containers.
  •  Identify the architecture of Kubernetes: pods, namespaces.
  •  Create Docker containers using Google Container Builder.
  •  Store container images in Google Container Registry.
  •  Create a Kubernetes Engine cluster.
  •  Manage Kubernetes deployments.
Module 3: Introduction to AI Platform Pipelines
  •  Identify the benefits and opportunities of AI Pipelines.
  •  Define Access Controls within AI Pipelines.
  •  Recognize pipeline components.
  •  List pipeline workflows.
  •  Set up AI Platform Pipelines.
  •  Create a machine learning pipeline.
  •  Run a machine learning pipeline.
  •  Connect to AI Platform Pipelines using the Kubeflow Pipelines SDK.
  •  Configure a Google Kubernetes Engine cluster for AI Platform Pipelines.
Module 4: Training, Tuning and Serving on AI Platform
  •  Identify the main concepts of MLOps on AI Platform.
  •  Create a reproducible dataset.
  •  Implement a tunable model.
  •  Build and push a training container.
  •  Train and tune a model.
  •  Serve and query a model.
Module 5: Kubeflow Pipelines on AI Platform
  •  Recognize how Kubeflow Pipelines fits in MLOps.
  •  Describe a Kubeflow Pipeline with KF DSL.
  •  Use the various Kubeflow components.
  •  Compile, upload, and run a pipeline build in Kubeflow Pipelines.
Module 6: CI/CD for Kubeflow Pipelines on AI Platform
  •  Create Cloud Build Builders.
  •  Configure pipelines with Cloud Build.
  •  Create triggers for training models using Cloud Build Triggers.
  •  Adopt the best CI/CD practices in the context of ML systems.
  • Module 7: Summary
  •  Summarize the course
This course is not associated with any certification.

Frequently Asked Questions (FAQs)

  • Why get Google Cloud Platform (GCP) certified?

    Google Cloud certifications validate your expertise in cloud technologies and your proficiency in using Google Cloud Platform's vast array of services.

    These certifications are recognized globally and highly sought after by employers, as they demonstrate your ability to design, develop, and manage scalable and secure cloud solutions on GCP.

    Google Cloud-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    Google Cloud offers a variety of certification exams across different levels (Foundational, Associate, and Professional) covering various job roles and specializations.

    The exams typically consist of multiple-choice and multiple-select questions, as well as scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Google Cloud Platform (GCP) certification valid for?

    Most Google Cloud certifications, including Professional-level certifications, are valid for two years from the date of passing the exam.

    The Cloud Digital Leader and Associate Cloud Engineer certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the same exam or an equivalent higher-level certification exam before your current certification expires.

    You will receive a notification from Google Cloud prior to your certification's expiration date.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 16 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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Exam & Certification

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