- Course
(GCP-PMLE) Architecting Low-code AI Solutions
Gain the expertise to build scalable AI solutions with minimal coding. This course will teach you to leverage BigQuery ML, Google Cloud AI APIs, and AutoML to develop powerful models, implement RAG, and solve business problems efficiently.
Intermediate
- Course
(GCP-PMLE) Architecting Low-code AI Solutions
Gain the expertise to build scalable AI solutions with minimal coding. This course will teach you to leverage BigQuery ML, Google Cloud AI APIs, and AutoML to develop powerful models, implement RAG, and solve business problems efficiently.
Intermediate
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This course is included in the libraries shown below:
- Cloud
- Data
What you'll learn
Are you looking to unlock AI/ML capabilities on Google Cloud without getting bogged down in complex infrastructure and training code? Or perhaps you are preparing for the Google Cloud Professional Machine Learning Engineer certification exam? In this course, (GCP-PMLE) Architecting Low-code AI Solutions, you’ll learn to utilize Google Cloud’s low-code and no-code tools to build robust machine learning models and generative AI applications. First, you will discover how to develop ML models directly where your data resides using BigQuery ML. Next, you will explore building AI solutions using ML APIs and foundational models. Finally, you’ll master training models using AutoML. When you’re finished with this course, you’ll have the skills and knowledge needed to architect effective low-code AI solutions and will be fully prepared for the first section of the Professional Machine Learning Engineer exam.
(GCP-PMLE) Architecting Low-code AI Solutions
Intermediate
Table of contents
IT professional with a PhD in Software-Defined Networking and certified Cloud Architect on Microsoft Azure and Google Cloud Platform (GCP). With a background ranging from software development and systems engineering to professional services for Cloud migration, I have accumulated experience in Hybrid cloud infrastructure, cloud architecture and design, Infrastructure-as-Code (IaC) as well as Agile/DevOps practices. My current interests involve AI / Machine Learning and Internet-of-Things. (IoT).
