ML and AI on Google Cloud
Learn to implement machine learning in data pipelines using Google Cloud's tools including AutoML, Notebooks, and BigQuery ML for enhanced business insights.
Learn to implement machine learning in data pipelines using Google Cloud's tools including AutoML, Notebooks, and BigQuery ML for enhanced business insights.
This comprehensive course explores the integration of machine learning into data pipelines on Google Cloud Platform. Students learn various implementation approaches based on customization needs, from AutoML for simplified solutions to BigQuery ML for specialized requirements. The course covers essential concepts in ML, AI, and Deep Learning, practical applications using ML APIs for unstructured data, and hands-on experience with Notebooks and Vertex AI. Through QwikLabs, participants gain practical skills in building and deploying ML models, making this course ideal for those looking to enhance their data engineering capabilities with machine learning.
Instructors:
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What you'll learn
Differentiate between Machine Learning, AI, and Deep Learning concepts and applications
Implement ML APIs effectively for processing unstructured data
Create and execute BigQuery commands within Notebooks environment
Develop ML models using SQL syntax in BigQuery
Build custom ML models without coding using AutoML
Deploy production-ready ML pipelines on Google Cloud
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 9 modules in this course
This course provides a comprehensive introduction to implementing machine learning solutions on Google Cloud Platform. It covers various approaches to incorporating ML into data pipelines, from using pre-built ML APIs and AutoML for quick solutions to more customized implementations using BigQuery ML and Vertex AI. The course emphasizes hands-on learning through QwikLabs, teaching participants how to build, train, and deploy ML models effectively. Key topics include differentiating between ML, AI, and Deep Learning, working with unstructured data using ML APIs, executing BigQuery commands in Notebooks, and creating ML models using both SQL syntax and AutoML approaches.
Introduction
Module 1
Introduction to Analytics and AI
Module 2
Prebuilt ML Model APIs for Unstructured Data
Module 3
Big Data Analytics with Notebooks
Module 4
Production ML Pipelines
Module 5
Custom Model Building with SQL in BigQuery ML
Module 6
Custom Model Building with AutoML
Module 7
Summary
Module 8
Course Resources
Module 9
Fee Structure
Instructor
Empowering Businesses with Expert Training from Google Cloud
The Google Cloud Training team is tasked with developing, delivering, and evaluating training programs that enable our enterprise customers and partners to effectively utilize our products and solutions. Google Cloud empowers millions of organizations to enhance employee capabilities, improve customer service, and innovate for the future using cutting-edge technology built specifically for the cloud. Our products are designed with a focus on security, reliability, and scalability, covering everything from infrastructure to applications, devices, and hardware. Our dedicated teams are committed to helping customers successfully leverage our technologies to drive their success.
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