Google Professional Machine Learning Engineer

Master Machine Learning Skills for Real-World Impact

Master the core skills needed to excel as a Machine Learning Engineer with this in-depth course. Tailored to prepare you for the Google Cloud Professional Machine Learning Engineer certification exam, this program empowers you to design, build, and deploy effective ML models that solve real-world business problems using Google Cloud technologies.

Gain practical insights into production-grade ML workflows, industry best practices, and how this certification can accelerate your career in AI and data science.

Google Professional Machine Learning Engineer

AI Foundations on Google Cloud
AI Development on Google Cloud
ML Workflow and Vertex AI
Generative AI on Google Cloud

Vertex AI: Qwik Start
Dataprep: Qwik Start
Dataflow: Qwik Start – Templates
Dataflow: Qwik Start – Python
Dataproc: Qwik Start – Console
Dataproc: Qwik Start – Command Line
Cloud Natural Language API: Qwik Start
Speech-to-Text API: Qwik Start
Video Intelligence: Qwik Start
Prepare Data for ML APIs on Google Cloud: Challenge Lab

Mini-course: 8 lessons

Getting Started with BigQuery ML
Predict Visitor Purchases with a Classification Model
Predict Taxi Fare with a Forecasting Model
Bracketology with Google Machine Learning
Create ML Models with BigQuery ML: Challenge Lab

Creating a Data Transformation Pipeline with Cloud Dataprep
ETL Processing on Google Cloud Using Dataflow and BigQuery (Python)
Predict Visitor Purchases with a Classification Model
Engineer Data for Predictive Modeling: Challenge Lab

Introduction to Vertex AI Feature Store
Raw Data to Features
Feature Engineering
Preprocessing and Feature Creation
Feature Crosses: TensorFlow Playground
Introduction to TensorFlow Transform

Introduction to the TensorFlow Ecosystem
Design and Build an Input Data Pipeline
Building Neural Networks with TensorFlow and Keras
Training at Scale with Vertex AI

Architecting Production ML Systems
Designing Adaptable ML Systems
Designing High-Performance ML Systems
Hybrid ML Systems
Troubleshooting ML Production Systems

Employing Machine Learning Operations
Vertex AI and MLOps on Vertex AI

Introduction to Vertex AI Feature Store
An In-Depth Look

Mini-course: 1 lesson

Mini-course: 1 lesson

Mini-course: 5 lessons

Introduction to Model Evaluation
Model Evaluation for Generative AI

Introduction to TFX Pipelines
Pipeline Orchestration with TFX
Custom Components and CI/CD for TFX Pipelines
ML Metadata with TFX
Continuous Training with Multiple SDKs, Kubeflow & AI Platform Pipelines
Continuous Training with Cloud Composer
ML Pipelines with MLflow

Vertex AI: Qwik Start
Identify Damaged Car Parts with Vertex AutoML Vision
Deploy a BigQuery ML Customer Churn Classifier to Vertex AI
Vertex Pipelines: Qwik Start
Build and Deploy ML Solutions: Challenge Lab

Generative AI Applications
Prompts
Retrieval Augmented Generation (RAG)

AI Interpretability and Transparency
Modernizing Infrastructure in the Cloud

AI Interpretability and Transparency
Modernizing Infrastructure in the Cloud

AI Privacy
AI Safety

Why Choose This Certification?

Validates advanced skills in designing, building, and productionizing ML models using Google Cloud.
Official credential from Google Cloud—boosts your credibility in AI/ML hiring pipelines.
Recognized by top companies for deploying ML models at scale.
In-demand certification for roles involving MLOps and scalable ML systems.

Who Can Pursue This Certification ?

AI/ML professionals seeking specialization in Google Cloud.
Software engineers transitioning into machine learning.
Individuals aiming for roles in MLOps or production-grade AI.

Prerequisites

3+ years of industry experience, including 1+ year designing and managing ML solutions on Google Cloud.
Strong knowledge of Python, ML algorithms, TensorFlow or similar frameworks.
Familiarity with Google Cloud services like BigQuery, Vertex AI, Cloud Storage, etc.

Job Opportunities Available

Machine Learning Engineer (Google Cloud)
MLOps Engineer
AI Engineer (Cloud-based)
Data Scientist (Production ML)
AI/ML Consultant (GCP)

Key Benefits: What You Will Gain

Upon completing this certification path at Netsmartz School, learners gain practical confidence and role-ready capability.

Official Course Completion Badge/Certificate

Earn a prestigious course completion badge or certificate, available on the Netsmartz School and Microsoft, highlighting your proficiency in AI

Industry-Recognized Skills

Master key concepts and gain hands-on experience in Artificial Intelligence, making you well-equipped for real-world applications

Career Advancement

Enhance your career prospects by showcasing your expertise in AI to potential employers and staying ahead in today's rapidly evolving tech landscape

Google Professional Machine Learning Engineer certificate preview

Why Netsmartz School

Experts-led Classroom Trainings

Our programs are crafted with insights from top industry minds and educators, ensuring you gain skills that truly matter in the real world.

Hands-On Experience on Real-World Projects

Take on projects that mirror the real challenges of the industry, work with real data, and build practical skills that lead to job-ready expertise.

Insights from Industry Leaders

Gain valuable insights from leading practitioners who bring industry use cases, case studies, and proven strategies into your classroom

Guidance and Support from Mentors

Stay on track with 24/7 access to mentors and a community of peers, all ready to help you overcome any challenges along the way.

Google Professional Machine Learning Engineer

Master Machine Learning Skills for Real-World Impact

Gain practical insights into production-grade ML workflows, industry best practices, and how this certification can accelerate your career in AI and data science.

Google Professional Machine Learning Engineer

AI Foundations on Google Cloud
AI Development on Google Cloud
ML Workflow and Vertex AI
Generative AI on Google Cloud

Vertex AI: Qwik Start
Dataprep: Qwik Start
Dataflow: Qwik Start – Templates
Dataflow: Qwik Start – Python
Dataproc: Qwik Start – Console
Dataproc: Qwik Start – Command Line
Cloud Natural Language API: Qwik Start
Speech-to-Text API: Qwik Start
Video Intelligence: Qwik Start
Prepare Data for ML APIs on Google Cloud: Challenge Lab

Mini-course: 8 lessons

Getting Started with BigQuery ML
Predict Visitor Purchases with a Classification Model
Predict Taxi Fare with a Forecasting Model
Bracketology with Google Machine Learning
Create ML Models with BigQuery ML: Challenge Lab

Creating a Data Transformation Pipeline with Cloud Dataprep
ETL Processing on Google Cloud Using Dataflow and BigQuery (Python)
Predict Visitor Purchases with a Classification Model
Engineer Data for Predictive Modeling: Challenge Lab

Introduction to Vertex AI Feature Store
Raw Data to Features
Feature Engineering
Preprocessing and Feature Creation
Feature Crosses: TensorFlow Playground
Introduction to TensorFlow Transform

Introduction to the TensorFlow Ecosystem
Design and Build an Input Data Pipeline
Building Neural Networks with TensorFlow and Keras
Training at Scale with Vertex AI

Architecting Production ML Systems
Designing Adaptable ML Systems
Designing High-Performance ML Systems
Hybrid ML Systems
Troubleshooting ML Production Systems

Employing Machine Learning Operations
Vertex AI and MLOps on Vertex AI

Introduction to Vertex AI Feature Store
An In-Depth Look

Mini-course: 1 lesson

Mini-course: 1 lesson

Mini-course: 5 lessons

Introduction to Model Evaluation
Model Evaluation for Generative AI

Introduction to TFX Pipelines
Pipeline Orchestration with TFX
Custom Components and CI/CD for TFX Pipelines
ML Metadata with TFX
Continuous Training with Multiple SDKs, Kubeflow & AI Platform Pipelines
Continuous Training with Cloud Composer
ML Pipelines with MLflow

Vertex AI: Qwik Start
Identify Damaged Car Parts with Vertex AutoML Vision
Deploy a BigQuery ML Customer Churn Classifier to Vertex AI
Vertex Pipelines: Qwik Start
Build and Deploy ML Solutions: Challenge Lab

Generative AI Applications
Prompts
Retrieval Augmented Generation (RAG)

AI Interpretability and Transparency
Modernizing Infrastructure in the Cloud

AI Interpretability and Transparency
Modernizing Infrastructure in the Cloud

AI Privacy
AI Safety

Key Benefits: What You Will Gain

Upon completing this certification path at Netsmartz School, learners gain practical confidence and role-ready capability.

Official Course Completion Badge/Certificate

Earn a prestigious course completion badge or certificate, available on the Netsmartz School and Microsoft, highlighting your proficiency in AI

Industry-Recognized Skills

Master key concepts and gain hands-on experience in Artificial Intelligence, making you well-equipped for real-world applications

Career Advancement

Enhance your career prospects by showcasing your expertise in AI to potential employers and staying ahead in today's rapidly evolving tech landscape

Why Netsmartz School

Experts-led Classroom Trainings

Our programs are crafted with insights from top industry minds and educators, ensuring you gain skills that truly matter in the real world.

Hands-On Experience on Real-World Projects

Take on projects that mirror the real challenges of the industry, work with real data, and build practical skills that lead to job-ready expertise.

Insights from Industry Leaders

Gain valuable insights from leading practitioners who bring industry use cases, case studies, and proven strategies into your classroom

Guidance and Support from Mentors

Stay on track with 24/7 access to mentors and a community of peers, all ready to help you overcome any challenges along the way.