Google Cloud Arcade Facilitator '26 — Syllabus for the Program

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The Arcade Facilitator Program is a no-cost, gamified learning campaign for technical practitioners at every level. Participants can build practical Google Cloud and AI skills, earn shareable credentials, collect Arcade progress, and work toward program milestones.
Program starts: July 13, 2026 at 5:00 PM GMT+5:30
Program ends: September 14, 2026 at 11:59 PM GMT+5:30
Duration: Two months
The syllabus and active game links may be updated during the cohort. Always check the official page before starting a game.
Complete activities in the following order:
Arcade games first — they normally have monthly deadlines.
Time-limited special games — complete them before they disappear.
Skill badge courses — use the remaining program time to earn as many badges as possible.
Additional catalog badges — required when targeting the highest milestone.
Google normally releases six Arcade games each month. The monthly lineup can include:
Arcade Base Camp
Arcade Adventure
Arcade Voyage
Arcade Trail
A themed or certification-focused game
A special Arcade game
Across the two-month Facilitator cohort, participants can complete up to 12 monthly game badges.
For the highest Facilitator milestone, any 12 eligible game completions can be counted.
| Game | Link | Access code | Deadline |
|---|---|---|---|
| The Arcade Base Camp July 2026 | Open game | 1q-basecamp-07511 |
July 31, 2026 |
| Arcade Adventure: Low-Code Development | Open game | 1q-lowcode-92316 |
July 31, 2026 |
| Arcade Voyage: Cloud Storage and Data Governance | Open game | 1q-bucket-58231 |
July 31, 2026 |
| Arcade Trail: Google Workspace Administration | Open game | 1q-dataset-72501 |
July 31, 2026 |
| Arcade Simulator: Data Mesh Architect | Open game | 1q-datamesh-16451 |
July 31, 2026 |
| Safe Spaces | Open game | 1q-security-19110 |
July 31, 2026 |
Open each game and verify the displayed deadline and eligibility before beginning.
The Facilitator syllabus highlights 51 skill badges, divided into three learning tracks:
| Track | Number of badges |
|---|---|
| Beginner — Get Started with Google Cloud & AI | 17 |
| Intermediate — Dive Deeper into Google Cloud & AI | 17 |
| Advanced — Take Your Google Cloud & AI Skills to the Next Level | 17 |
| Total | 51 |
You may complete the badges in any order. Choose courses based on your current knowledge, available credits, and the technologies you want to practise.
Publishing note: The official page renders its badge accordions dynamically and Google may rename or replace courses during the cohort. The checklist below is a Markdown-friendly snapshot reconstructed from the currently indexed syllabus and Google Skills catalog. Verify newly added or renamed badges against the live syllabus before publishing an update.
Create Your First Gemini Enterprise Application (1 lab & 0 credits)
Develop AI-Powered Prototypes in Google AI Studio (4 labs & 0 credits)
The Basics of Google Cloud Compute (4 labs & 4 credits)
Implement Event-Driven Messaging and Automation Workflows (3 labs & 2 credits)
Implement Cloud Storage and Data Protection Solutions (4 labs & 4 credits)
Create a Streaming Data Lake on Cloud Storage (4 labs & 3 credits)
Deploy and Manage Applications on Google App Engine (4 labs & 4 credits)
Implement Speech and Language Solutions with Pre-trained APIs (4 labs & 4 credits)
Using the Google Cloud Speech API (4 labs & 4 credits)
Analyze Speech and Language with Google APIs (4 labs & 8 credits)
Store, Process, and Manage Data on Google Cloud - Console (4 labs & 3 credits)
Store, Process, and Manage Data on Google Cloud - Command Line (4 labs & 3 credits)
Migrate MySQL Data to Cloud SQL Using Database Migration Service (5 labs & 5 credits)❌
Get Started with Sensitive Data Protection (4 labs & 4 credits)
Analyze Images with the Cloud Vision API (4 labs & 12 credits)
Build Event-Driven Applications with Eventarc (4 labs & 3 credits)
Configure Service Accounts and IAM Roles for Google Cloud (4 labs & 4 credits)
Engineer AI Agents with Agent Development Kit (ADK) (1 lab & 5 credits)
Build Real World AI Applications with Gemini and Imagen (4 labs & 0 credits)
Build a Smart Cloud Application with Vibe Coding and MCP (4 labs & 4 credits)
Implement Cloud Collaboration and Productivity Workflows (7 labs & 0 credits)
Analyze BigQuery Data in Connected Sheets (4 labs & 0 credits)❌
Streaming Analytics into BigQuery (4 labs & 2 credits)
Create a Secure Data Lake on Cloud Storage (4 labs & 4 credits)
Secure Lakehouse Data (4 labs & 4 credits)
Enrich Metadata and Discovery of Lakehouse Data (4 labs & 3 credits)
Monitor and Manage Google Cloud Resources (4 labs & 4 credits)🚀
Monitor and Log with Google Cloud Observability (5 labs & 9 credits)
Set Up a Google Cloud Network (4 labs & 8 credits)
Integrate BigQuery Data and Google Workspace using Apps Script (4 labs & 2 credits)
Engineer Data for Predictive Modeling with BigQuery ML (4 labs & 15 credits)
Implement DevOps Workflows in Google Cloud (4 labs & 16 credits)
Create ML Models with BigQuery ML (5 labs & 11 credits)
Build a Website on Google Cloud (5 labs & 13 credits)
Explore Generative AI in Agent Platform (4 labs & 16 credits)
Implementing Cloud Load Balancing for Compute Engine (4 labs & 4 credits)
Prompt Design in Agent Platform (4 labs & 4 credits)
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG (4 labs & 20 credits)
Develop GenAI Apps with Gemini and Streamlit (5 labs & 20 credits)
Set Up an App Dev Environment on Google Cloud (10 labs & 8 credits)
Develop Your Google Cloud Network (6 labs & 18 credits)
Build a Secure Google Cloud Network (6 labs & 30 credits)
Deploy Kubernetes Applications on Google Cloud (4 labs & 12 credits)
Derive Insights from BigQuery Data (7 labs & 6 credits)
Build LookML Objects in Looker (5 labs & 0 credits)
Manage Data Models in Looker (6 labs & 0 credits)
Prepare Data for Looker Dashboards and Reports (5 labs & 0 credits)✔️
Develop Serverless Apps with Firebase (4 labs & 16 credits)
Cloud Architecture: Design, Implement, and Manage (6 labs & 32 credits)
Build Global and Regional Load Balancing Solutions (4 labs & 20 credits)
Google DeepMind: Train A Small Language Model (1 lab & 5 credits)
The official syllabus currently lists 51 skill badges.
To reach the highest Facilitator milestone, participants must also find and complete 15 additional eligible skill badges from the wider Google Skills catalog.
That means the target is:
51 listed skill badges
+ 15 additional catalog skill badges
= 66 skill badge completions
The game requirement is:
12 eligible Arcade game completions
Badge availability, course titles, eligibility rules, and milestone calculations may change. Use your Facilitator progress emails and the official syllabus as the final source of truth.
Use the same Google account for enrolment and Google Skills.
Make sure your Google Skills profile is public when the program requires profile validation.
Starting a lab is not enough; complete the full game or skill badge to earn its credential.
Do not create duplicate program registrations.
Complete monthly games before working through badges without deadlines.
Review progress emails and report incorrect or missing activity as early as possible.
Avoid relying only on unofficial videos or spreadsheets because game codes and requirements can change.
The syllabus is updated throughout the program. Bookmark the official page and check it regularly for new games, corrected access codes, and changes to eligible skill badges.
#GoogleCloud #GoogleSkills #GoogleCloudArcade #CloudComputing #GenerativeAI :::