Google Machine Learning and Generative AI for Solutions Architects
Build efficient and scalable AI/ML solutions on Google Cloud
Created by Kieran Kavanagh
Explore how to design, implement, and manage AI and machine learning workloads using Google Cloud. Gain practical experience with real-world use cases and hands-on projects, moving from foundational concepts to advanced generative AI applications. Learn to overcome common challenges and apply industry best practices for scalable solutions.
Packt | Jun 2024 | 552 min
What You Will Learn
You will start by building a solid understanding of core AI and machine learning concepts, then apply them using Google Cloud's suite of services. Through hands-on exercises and real-world scenarios, you'll practice preparing data, training models, deploying solutions, and automating workflows. Each step is supported by practical examples and proven industry patterns.
Key Features
- Design and deploy machine learning models using Google Cloud services and tools
- Implement MLOps strategies to automate and scale AI/ML workflows efficiently
- Apply generative AI patterns like Retrieval Augmented Generation and agentic workflows
Target Audience
Ideal for solutions architects and technical professionals with a basic grasp of Python and machine learning concepts. If you want to design and implement AI or generative AI solutions on Google Cloud, and are looking to bridge the gap between theory and real-world application, you'll find practical guidance and actionable skills to advance your expertise.
