A progress tracking dashboard for Google Cloud Learn with Communities 2026 (GDGC-JISU1 community).
# Drop your daily CSV into data/raw/, then run:
python scripts/ingest_csv.py
# Or specify a CSV directly:
python scripts/ingest_csv.py "path/to/GDGC-JISU1 [30 Oct].csv"# Start a local server:
python -m http.server 8080
# Open in browser:
# http://localhost:8080| # | Skill Badge Name | URL | Credits |
|---|---|---|---|
| 1 | The Basics of Google Cloud Compute | Link | 4 |
| 2 | Configure Service Accounts and IAM Roles for Google Cloud | Link | 4 |
| 3 | Implement Speech and Language Solutions with Pre-trained APIs | Link | 4 |
| 4 | Develop AI-Powered Prototypes in Google AI Studio | Link | 0 |
| 5 | Analyze Images with the Cloud Vision API | Link | 12 |
| 6 | Build a Website on Google Cloud | Link | 13 |
| 7 | Create Your First Gemini Enterprise Application | Link | 0 |
| 8 | Store, Process, and Manage Data on Google Cloud - Console | Link | 3 |
| 9 | Using the Google Cloud Speech API | Link | 4 |
| 10 | Explore Generative AI in Agent Platform | Link | 16 |
| Total | All 10 Badges | 60 credits |
Note
Every student receives 200 credits. Completing all 10 badges only takes 60 credits, leaving 140 spare credits for lab retries or practice.
- Download the CSV from your daily Google email
- Save it to
data/raw/ - Run
python scripts/ingest_csv.py - Refresh
http://localhost:8080
Learn_with_communities/
├── index.html # Clean, professional dashboard (HTML/JS/Tailwind)
├── data/
│ ├── raw/ # Drop daily CSVs here
│ ├── latest.json # Current data + curriculum metadata
│ └── history.json # Historical snapshots for trend lines
├── scripts/
│ └── ingest_csv.py # CSV parser & metric processor
└── README.md
- Deadline: 23 November 2026 (No extensions provisioned)
- Daily Lab Limit: Maximum 15 labs completed per day
- Total Badges Required: 10 Skill Badges
- Credit Allocation: 200 credits total per participant