Introduction to Vertex AI Notebooks for Cloud Data Science

Cloud-based notebooks are the cornerstone of modern data science, offering scalable compute resources without local setup hassle. This written course guides you through configuring and utilizing Vertex AI Notebooks to streamline your machine learning experiments. You will transition from running local experiments to managing secure, cloud-hosted Jupyter environments. You will learn to handle data, write clean code, and integrate modern MLOps principles directly within your cloud workspace. What you'll learn: 1. Understand Vertex AI notebook instances and basic cloud infrastructure concepts. 2. Configure and customize JupyterLab environments for data science workloads. 3. Manage data ingestion and storage using modern dataframe libraries and cloud storage buckets. 4. Apply basic MLOps workflows to version and track your experimental runs. 5. Write clean, structured Python code optimized for cloud-based computing resources. Starting with basic environment setup and core cloud concepts, the text-guided lessons walk you through data exploration, model prototyping, and best practices for resource management. This course is designed for aspiring data scientists, analysts, and developers new to cloud-hosted development environments, with no prior cloud experience required. Start reading today to elevate your data science workflow to the cloud.