%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
Machine Learning Engineer Learning Path
Overview :
Google Cloud's Machine Learning Engineer Learning Path is a curated set of online courses and labs designed to equip learners with practical hands-on experience in Google Cloud technologies. It covers key skills in designing, building, deploying, optimizing, running, and maintaining machine learning systems. Upon completion of this learning path, learners can further pursue the Google Cloud Machine Learning Engineer certification, laying a solid foundation for career advancement.
Target Users :
Suitable for individuals or teams looking to build and deploy machine learning solutions on the Google Cloud platform, especially data scientists, AI developers, and machine learning engineers.
Use Cases
Build a machine learning model without code using Vertex AI AutoML
Design and optimize machine learning models using TensorFlow and Keras
Apply machine learning workflows to solve real-world problems in an enterprise environment
Utilize MLOps tools and practices to deploy and manage production-level machine learning systems
Features
Google Cloud Platform Basic Function Operations
Introduction to AI and Machine Learning Services
Data Quality Improvement and Exploratory Data Analysis
Building, Training, and Deploying Machine Learning Models Using Vertex AI AutoML
TensorFlow and Keras Model Design
Improving Machine Learning Model Accuracy
Scaling Machine Learning Model Usage
Feature Engineering
Enterprise-Grade Machine Learning Workflows
Production-Ready Machine Learning System Implementation
Computer Vision Fundamentals
Natural Language Processing
Recommendation System Building
Introduction to Machine Learning Operations (MLOps)
MLOps Tools and Practices
Building Machine Learning Pipelines
Preparing Data for ML APIs
Building and Deploying Machine Learning Solutions on Vertex AI
Featured AI Tools
Pseudoeditor
PseudoEditor is a free online pseudocode editor. It features syntax highlighting and auto-completion, making it easier for you to write pseudocode. You can also use our pseudocode compiler feature to test your code. No download is required, start using it immediately.
Development & Tools
3.8M
Coze
Coze is a next-generation AI chatbot building platform that enables the rapid creation, debugging, and optimization of AI chatbot applications. Users can quickly build bots without writing code and deploy them across multiple platforms. Coze also offers a rich set of plugins that can extend the capabilities of bots, allowing them to interact with data, turn ideas into bot skills, equip bots with long-term memory, and enable bots to initiate conversations.
Development & Tools
3.8M