Cloud Infrastructure

GCPMLE : Preparing for Professional Machine Learning Engineer

Course Duration

1 Day

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

What You'll Learn

Explain the value of the Google PMLE certification
Describe the role of a Professional Machine Learning Engineer
Explain what Cymbal Retail is, and how the company will be used throughout the course.
Identify resources to support your certification journey
Identify your level of knowledge in developing and implementing BigQuery ML and AutoML machine learning solutions.
Determine the skills needed to select appropriate ML APIs, prepare data effectively, and build custom models using AutoML.
Identify your level of knowledge in exploring, preprocessing, and managing organization-wide data.
Identify your level of knowledge in addressing privacy implications and leveraging tools like Vertex AI Feature Store.
Determine the skills needed to prototype models using Jupyter notebooks on Google Cloud.
Determine the skills needed to select appropriate backends, implement security best practices, and integrate with code repositories.
Identify your level of knowledge in scaling ML prototypes into production-ready models
Identify your level of knowledge in selecting appropriate ML frameworks, model architectures, and modeling techniques based on interpretability requirements.
Determine the skills needed to train models effectively, including organizing and ingesting training data on Google Cloud.
Determine the skill needed to utilize distributed training techniques, perform hyperparameter tuning, and troubleshoot training failures.
Identify the level of knowledge needed to effectively serve models in production.
Identify the level of knowledge needed to select between batch and online inference, utilize various serving frameworks, organize a model registry, and conduct A/B testing for model optimization.
Determine the skills needed to scale online model serving, including leveraging Vertex AI Feature Store.
Determine the skills needed to manage public and private endpoints, choose appropriate hardware, optimize serving backends for throughput, and fine-tune models for optimal performance in production.
Identify the level of knowledge needed to develop and maintain end-to-end ML pipelines.
Identify the level of knowledge needed to validate data and model, consistent preprocessing, hosting options, component identification, parameterization, triggering mechanisms, compute needs, orchestration strategies.
Determine the skills needed to automate model retraining, including establishing retraining policies.
Determine the skills needed to implement CI/CD model deployment, and track and audit metadata (model artifacts, versions, data lineage).
Identify the level of knowledge needed to assess and mitigate risks in ML solutions.
Identify the level of knowledge needed to build secure ML systems, align with responsible AI practices, evaluate solution readiness, and utilize model explainability on Vertex AI.
Determine the skills needed to monitor, test, and troubleshoot ML solutions.
Determine the skills needed to establish continuous evaluation metrics, monitor for training-serving skew and feature drift, compare model performance against baselines, and investigate common training and serving errors.
Review a sample study plan for the exam
Learn how to register for the exam

Who Should Attend

Googlers, partners, and customers

Prerequisites

Learning Journey

Coming Soon...

Module 0 – Introduction

Topics

Course agenda
Module agenda
The value of Google PMLE certification
The role of an PMLE
About the Cymbal Retail (fictional company used in the course)
Resources to support your certification journey
Creating a study plan

Module 01 - Architecting low-code AI solutions

Topics

Ira needs to understand customer segments using BigQuery and
a clustering model.
Sasha needs to predict customer value using AutoML Cymbal Retail’s
customer dataset.
Taylor needs to build a conversational AI assistant for customers using Vertex AI
Agent Builder and retrieval-augmented generation (RAG)
Diagnostic questions
Review and study planning

Module 02 - Collaborating within and across teams to manage data and models
Topics

Use Google Cloud's products and Cymbal Retail's rich data to design a model
to predict which high-value customers are likely to stop purchasing (also known as
customer churn).
Answer diagnostic questions.
Review the information and plan your study.

Module 03 - Scaling prototypes into ML models
Topics

Use Google Cloud's products and Cymbal Retail's rich data to build and scale
customer churn prototype into a production-ready model
Answer diagnostic questions.
Review the information and plan your study.

Module 04 - Serving ML models
Topics

Use Google Cloud's products and Cymbal Retail's rich data to deploy a customer
churn model and use it in production for inference.
Answer diagnostic questions.
Review the information and plan your study.

Module 05 - Automating and orchestrating ML pipelines
Topics

Use Google Cloud’s products to orchestrate the entire machine learning pipeline
for seamless execution and continuous improvement with customer churn.
Answer diagnostic questions.
Review the information and plan your study.

Module 06 - Monitoring ML Solutions
Topics

Use Google Cloud’s products to ensure the customer churn model remains robust,
reliable, and aligned with Google’s Responsible AI principles.
Answer diagnostic questions.
Review the information and plan your study.

Module 07 - Your next steps
Topics

A sample study plan for the exam
How to register for the exam

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 24 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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Cloud Infrastructure

GCPMLE : Preparing for Professional Machine Learning Engineer

What You'll Learn

Who Should Attend

Prerequisites

Learning Journey

Frequently Asked Questions (FAQs)

Why get Google Cloud Platform (GCP) certified?

What to expect for the examination?

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

Why take this course with Trainocate?

Keep Exploring

Course Curriculum

Training Schedule

Exam & Certification

Frequently Asked Questions

Improve yourself and your career by taking this course.

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