Google Cloud Professional – Machine Learning Engineer

This Skill Validation program verifies your ability to build, train, optimize, and deploy Machine Learning solutions on Google Cloud Platform (GCP). Based on real-world workflows from Hands-On Machine Learning on Google Cloud Platform, the course assesses your competence across data preparation, model development, neural networks, TensorFlow/Keras, hyperparameter tuning, and production deployment.

Through practical, scenario-based tasks and chapter-wise quizzes, you prove mastery of essential skills such as using GCP ML APIs, training deep learning models, preventing overfitting, evaluating performance with TensorBoard, and deploying scalable ML applications.

By completing this course, you demonstrate job-ready expertise in applying ML on Google Cloud to solve real industry problems.

Design scalable and secure architectures on Google Cloud.
Implement IAM, security controls, and least-privilege access.
Build and operate cloud networks, compute workloads, and storage systems.
Automate deployments using DevOps and infrastructure-as-code practices.
Use BigQuery and data pipelines for analytics and data processing.
Build, train, and optimize machine learning models on Google Cloud.
Integrate AI/ML APIs into applications for vision, NLP, and speech tasks.
Develop serverless and container-based applications.
Build conversational and generative AI solutions using Google Cloud tools.
Troubleshoot, monitor, and optimize cloud workloads effectively.

Cloud Engineers, Solutions Architects, and SysOps Professionals who want to validate their hands-on Google Cloud expertise.
Security Engineers and DevOps Practitioners who need to strengthen cloud security, automation, and operations knowledge.
IT Administrators and System Engineers transitioning from on-prem environments to Google Cloud.
Data Engineers and Machine Learning Practitioners seeking structured cloud-based deployment and MLOps understanding.
Professionals preparing for Google Cloud certification who want practical, scenario-based skill validation.

Course Content

Foundations of Google Cloud Architecture

Foundations of Google Cloud Architecture
Foundations of Google Cloud Architecture

Designing and Managing Virtual Machine Workloads

Architecting Cloud Storage Solutions

BigQuery Analytics & Data Warehouse Engineering

Data Processing and ETL on Google Cloud

Core Machine Learning Foundations in the Cloud

Applied AI with Pretrained Cloud APIs

Mobile & Web ML Integration Using Firebase

Building Neural Networks with TensorFlow/Keras

Model Evaluation and Visualization with TensorBoard

Hyperparameter Optimization Strategies

Model Regularization & Generalization Techniques

Deep Learning with CNNs and RNNs

Time Series Forecasting Using LSTM Models

Applied Reinforcement Learning Concepts

Generative AI with GANs and Variational Models

Conversational AI Systems with Google Cloud

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Google Cloud Professional – Machine Learning Engineer – Basics

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