Course Overview
This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects.
It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
What are the skills covered
- Recognize the data-to-AI technologies and tools provided by Google Cloud
- Build generative AI projects by using Gemini multimodal, efficient prompts, and model tuning
- Explore various options for developing an AI project on Google Cloud
- Create an ML model from end-to-end by using Vertex AI.
Who should attend this course
Professional AI developers, data scientists, and ML engineers who want to build predictive and generative AI projects on Google Cloud
Course Curriculum
Course Modules
Exam & Certification
Google Certified Associate Data Practitioner.
The Associate Data Practitioner secures and manages data on Google Cloud. This individual has experience using Google Cloud data services for tasks like data ingestion, transformation, pipeline management, analysis, machine learning, and visualization. Candidates have a basic understanding of cloud computing concepts like infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS).
This course along with GCP-IDEGC: Introduction to Data Engineering on Google Cloud prepares you for the Associate Data Practitioner certification.
