Getting Started with Vector Search and Embeddings

Google Cloud, located in Toronto, North America, offers you a unique blend of academic and professional opportunities. As a institution founded in 2008, it provides a fresh perspective on education. You will find advantages in its strong focus on computing, data storage, and machine learning, making it an ideal choice for students interested in these fields. Its client base spans various industries, including financial services, healthcare, retail, and education, providing you with a broad range of potential collaborations and career paths.

Specifically, Google Cloud focuses on services like computing, data analytics, and machine learning, with tools such as Google Cloud Platform (GCP) and Google Workspace. You can choose from 723 programs, which cover a broad spectrum of subjects. Key languages and technologies are taught, preparing you for a career in these in-demand fields. For instance, you can develop skills in Gmail, Docs, Drive, and Calendar, making you proficient in Google's suite of productivity tools.

In Toronto, you will find a unique city benefit - a diverse and thriving metropolis with many opportunities for internships, collaborations, and networking. You can take advantage of the city's active startup scene, with many companies using Google Cloud services. On campus, you can engage with a community of 30,000 students, including many international students, creating a dynamic and global learning environment. Opportunities for you include accessing modern labs, and participating in active student clubs, making your time at Google Cloud a rich and rewarding experience.

This program is a self-paced lab for students who want to learn about vector search and embeddings, offered by Google Cloud in English. It's a non-degree program that lasts several weeks and helps you find similar documents based on their text content.

The curriculum includes hands-on experience with text embeddings and Vertex AI vector search in the Google Cloud console. You will learn to use these tools to search for similar documents, developing skills in data analysis and machine learning.

After completing this program, you can pursue careers as a Data Analyst, Machine Learning Engineer, or Cloud Architect, working with companies like Google or other tech firms. You can also work as a Data Scientist or a Research Scientist, applying your skills in vector search and embeddings to real-world problems.