What is Vertex AI Academy?

Vertex AI Academy is the #1 free interactive learning platform by Infinity Tech Stack for Google Cloud Vertex AI and the Gemini model family. It covers Gemini 4 Argon, Gemini 3.8 Flash, Gemini 3.8 Live, Gemini 3.6 Flash, Gemini 3.5 & 3.1 Flash-Lite, Context Caching, Grounding with Google Search, Vertex AI Agent Engine (ADK), and Remote MCP across 13 modules, 33 lessons, 33 gcloud CLI labs, and 79 quizzes with zero sign-up required.

How is Infinity Vertex AI Academy different from Google Cloud Skills Boost?

Unlike Google Cloud Skills Boost which requires GCP cloud credentials, project setup, and credits, Infinity Tech Stack's Vertex AI Academy is 100% free with 33 in-browser terminal simulations and 79 quizzes covering Gemini 4 Argon, Gemini 3.8 Flash, Context Caching, Google Search Grounding, BigQuery ML (AI.GENERATE & ML.GENERATE_TEXT), and Google ADK with no sign-up or credit card required.

How long does Vertex AI Academy take to complete?

Vertex AI Academy contains approximately 3 to 5 hours of hands-on interactive training across 13 modules and 33 lessons. Progress is saved locally in your browser so you can learn at your own pace.

Is the Vertex AI Academy free?

Yes, it is 100% free with no sign-up required. All 13 modules, 33 lessons, 33 gcloud CLI labs, and 79 quizzes are immediately accessible. Progress is saved locally in your browser.

What topics does the Vertex AI course cover?

The course covers the Vertex AI platform, Gemini 4 Argon (with 1M context and up to 1M Long Decode output), Gemini 3.8 Flash, Gemini 3.8 Live, Gemini 3.6 Flash, Gemini 3.5 & 3.1 Flash-Lite, Nano Banana 2.1, Deep Think reasoning, Implicit & Explicit Context Caching, BigQuery ML (AI.GENERATE & ML.GENERATE_TEXT), Grounding with Google Search, Model Garden (including Claude 5.x), and Vertex AI Agent Engine / ADK.

What is Context Caching in Vertex AI?

Context Caching reduces latency and input token costs by up to 90%–95% on repeated large contexts (minimum 4,096 tokens on Gemini 3.x and 4 models). Vertex AI supports automatic Implicit Caching (enabled by default on Gemini 3.x and Gemini 4 Argon with zero hourly storage fees) as well as Explicit Caching (cachedContents with configurable TTLs on Gemini 3.x models).

What is Grounding with Google Search?

Grounding connects Gemini to live Google Search results, enabling the model to provide up-to-date, factual responses with source citations - reducing hallucinations in production applications.

Do I need a Google Cloud account?

No account is needed to take the course. The built-in browser labs simulate the gcloud CLI so you can practice without a GCP account; if you want to follow along for real, a GCP free tier account is sufficient for most exercises.

Does the Vertex AI Academy include hands-on labs?

Yes. 33 hands-on terminal labs are built into the lessons - authenticate with gcloud, enable the Vertex AI API, call Gemini via REST, and run Google's Agent Development Kit using real, vendor-verified commands, with objectives, hints, solutions, and XP rewards. No sign-up needed.

What is Deep Think in Gemini?

Deep Think is Gemini's extended reasoning mode that allocates additional compute for complex multi-step problems - similar to chain-of-thought reasoning - producing more accurate results for math, coding, and scientific analysis.

The Gemini 2.0 Generation Transition — Advanced RAG & Migration

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SEQ. 1

SEQ. 2

The Gemini 2.0 Generation Transition

⚙️ Advanced RAG & Migration 10m 200 BASE XP⌨ HANDS-ON LAB

Enterprise Lifecycle: Migrating from Legacy 1.5/2.0/2.5 to Gemini 3.8 & Gemini 4 Argon

Vertex AI enforces strict enterprise model and SDK retirement schedules (unlike consumer AI Studio grace periods). Keeping production workloads aligned with active generations prevents hard API outages:

2026 Vertex AI Retirement & Migration Matrix

Model Retirements on Vertex AI: Gemini 1.5 Pro/Flash retired in 2025; Gemini 2.0 Flash / Flash-Lite shut down in June 2026; and Gemini 2.5 Pro, 2.5 Flash & 2.5 Flash-Lite (including fine-tuned 2.5 variants) officially retired on October 20, 2026. Migrate flagship reasoning to gemini-4-argon, agentic coding to gemini-3.8-flash / gemini-3.6-flash, real-time voice to gemini-3.8-live, and high-throughput routing to gemini-3.5-flash-lite / gemini-3.1-flash-lite.
Unified SDK Migration (June 24, 2026 Removal): The legacy vertexai.generative_models module in google-cloud-aiplatform was deprecated on June 24, 2025 and removed on June 24, 2026. Standardize on pip install google-genai using from google import genai and client = genai.Client(vertexai=True, project="...", location="global").
Caching & Model Garden Synergy: Combine 4,096+ token Context Caching (90%–95% input savings; automatic implicit caching on gemini-4-argon) with Model Garden partner endpoints such as Anthropic Claude 5 / 5.5 (Sonnet & Opus) under unified GCP governance.

⌨ HANDS-ON LABVerify Gemini 3.8 Flash / 4 Argon Endpoint Readiness

⭐ +150 XP

Issue a healthcheck ping to the production Gemini 3.8 Flash publisher model on Vertex AI.

1Send a minimal generation ping to gemini-3.8-flash.

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$

OBJECTIVE 1 / 1 — type "hint" if stuck

SYNAPSE VERIFICATION

QUERY 1 // 1

Which SDK and model migrations are mandatory for production Vertex AI workloads as of late October 2026?

Stay on vertexai.generative_models and gemini-2.5-pro indefinitely

Migrate from removed vertexai.generative_models (June 24, 2026) to google-genai, and from retired Gemini 2.0/2.5 (June & Oct 20, 2026) to Gemini 3.8 Flash or Gemini 4 Argon

Switch all GCP authentication to unencrypted HTTP

Disable IAM roles