This repository provides sample code, scripts, and links for Google Cloud Platform (GCP) courses, covering essential services, enterprise solutions, AI/ML, and developer tools. It is designed for learners and practitioners seeking practical examples and guidance for using GCP, particularly those following the author's LinkedIn Learning courses.

How It Works

The project leverages GCP's native command-line tools (gcloud, gsutil, bq) and the Python SDK for interacting with various GCP services. Examples demonstrate practical application across storage, databases, big data, and machine learning, often referencing external resources like Qwiklabs for hands-on practice and official documentation for deeper dives.

Quick Start & Requirements

• Installation: No direct installation required; code is for demonstration and learning.
• Prerequisites: Access to a Google Cloud Platform account and the gcloud CLI tool.
• Resources: Requires a GCP project with billing enabled for executing commands. Links to official GCP documentation and the gcloud SDK are provided.

Highlighted Details

• Comprehensive coverage of GCP services, including storage, databases, big data, AI/ML, and cost control.
• Direct links to multiple LinkedIn Learning courses for structured learning paths.
• Curated list of external resources, including GCP cheat sheets, Qwiklabs, and other relevant GitHub repositories.
• Examples utilize gcloud, gsutil, bq, and the Python SDK for GCP.

Maintenance & Community

This repository is maintained by Lynn Langit, an instructor with multiple GCP-focused courses on LinkedIn Learning. Further community engagement or roadmap details are not explicitly mentioned in the README.

Licensing & Compatibility

The repository's content is presented as sample code and notes. The specific license is not stated, but the open-source nature implies free use for learning and experimentation. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The repository serves as supplementary material for courses and may not represent production-ready code. Users are responsible for managing their GCP resources and associated costs. Some links may point to external platforms or specific course versions.