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 3.8 Flash, Gemini 3.5 Flash-Lite, Context Caching, Grounding with Google Search, Managed Agents, and Remote MCP across 13 modules, 33 lessons, and 54+ quizzes with hands-on gcloud labs and 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 in-browser terminal simulations covering Gemini 3.8 Flash, Context Caching, Google Search Grounding, BigQuery ML, 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 2 to 3 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, lessons, and 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 3.8 Flash, Gemini 3.5 Flash-Lite, Gemini 2.5 Pro, Deep Think reasoning, 1M+ token Context Windows, Context Caching, BigQuery ML, Grounding with Google Search, Vertex AI Studio, and Agent Builder.

What is Context Caching in Vertex AI?

Context Caching lets you store large context payloads (documents, system prompts) server-side and reuse them across multiple requests, reducing latency and cost by up to 75% for repetitive workloads.

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. 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.

What is the specialized Gemini 3.8 variant designed for vulnerability detection and automated patching?

Gemini 3.8 Flash Cyber — Gemini 3.8 Flash Cyber is Google's specialized model for cybersecurity tasks and automated patching, available via the Fairwind Program.

What is the context window and max output token limit for Gemini 3.8 Flash?

1,048,576 (1M) context / 65,536 (64K) max output — Gemini 3.8 Flash supports a 1,048,576 token context window and up to 65,536 output tokens.

Under an AOE operational model on Vertex AI, what token threshold activates Context Caching for 75% savings?

32,768 tokens — On Vertex AI, Context Caching is supported for requests with 32,768 tokens or more, providing a 75% input token discount on cached data.

Gemini 1.5 Pro vs Flash Tutorial | Mastering the Gemini API

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Gemini 1.5 Pro vs Flash

✨ Mastering the Gemini API 10m 200 BASE XP⌨ HANDS-ON LAB

Choosing Your Engine

Google Cloud Vertex AI provides an enterprise hierarchy of Gemini models optimized across intelligence, reasoning depth, latency, and cost:

Gemini 3.8 Flash (Featured Workhorse - September 2, 2026): gemini-3.8-flash is Google's most intelligent workhorse model, launched September 2, 2026, built specifically for long-horizon coding and autonomous agentic workflows. Priced at $0.75 / $3.75 per million tokens, it features a 1,048,576 (1M) token context window, 65,536 max output tokens, native multimodal understanding, and configurable thinking levels (LOW, MEDIUM default, HIGH).
Gemini 3.8 Flash Cyber (September 2, 2026): A specialized security-focused variant engineered for automated vulnerability discovery, penetration testing analysis, and verified patch generation, available to trusted enterprise defenders via Google's Fairwind Program.
Gemini 3.5 Flash-Lite: gemini-3.5-flash-lite is the fast, budget-friendly tier engineered for high-volume, latency-sensitive production workloads, capable tool orchestration, and precise document understanding.
Gemini 3.5 Flash: gemini-3.5-flash delivers near-Pro intelligence at Flash-tier cost and speed, excelling in parallel agent execution.
Gemini 2.5 Pro: gemini-2.5-pro is Google's high-capability reasoning model for complex mathematics, architectural design, and deep coding with a 1M token context.
Gemini 3.1 Flash Image (Nano Banana 2): gemini-3.1-flash-image provides native image generation and conversational editing with SynthID watermarking.
Gemini Omni Flash: gemini-omni-flash-preview generates and edits 720p video natively from text and image prompts.

🚀 Featured Model: Gemini 3.8 Flash represents the flagship workhorse for developer workflows on Google Cloud Vertex AI, delivering frontier-level software engineering and agentic reasoning at Flash-tier efficiency ($0.75 in / $3.75 out per MTok).

⚡ Thinking Configuration: On Gemini 3.8 Flash, thinking is enabled by default with thinking_level="MEDIUM". You can dial it down to LOW for speed or up to HIGH for deep logic. Note: MINIMAL is not supported on 3.8 Flash.

September 2026 Platform Update: Agent Platform Workbench v2

On September 8, 2026, Google Cloud released updates to the Vertex AI Agent Platform Workbench (v2), including strict validation for scheduled upgrade metadata across agent runtimes and automated migration probes. This ensures enterprise multi-agent topologies seamlessly receive runtime patch updates without connection dropouts.

SOE & AOE Operational Runbook for Vertex AI

Enterprise deployments must implement robust Standard Operating Environments (SOE) and AI Operations Engineering (AOE):

SOE Standard: Authenticate exclusively via Google Application Default Credentials (ADC) or Workload Identity Federation; pin the unified google-genai SDK (replacing legacy google-generativeai / vertexai); isolate model endpoints behind VPC Service Controls (VPC-SC) perimeter policies.
AOE Context Management: Enforce Context Caching for prompts exceeding 32,768 tokens (yielding a 75% input discount); set deterministic TTLs (minimum 1 hour); instrument OpenTelemetry tracing exported directly to Google Cloud Trace; monitor Grounding freshness against Vertex AI Search datastores.

⌨ HANDS-ON LABCall Gemini Flash via REST

⭐ +150 XP

Benchmark time. Hit the generateContent endpoint for Gemini Flash directly with curl, authenticated by a gcloud access token.

1Store an access token in a shell variable using gcloud auth print-access-token.

2POST to the Gemini generateContent endpoint with curl (any gemini-* model ID).

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
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OBJECTIVE 1 / 2 — type "hint" if stuck

SYNAPSE VERIFICATION

QUERY 1 // 4

Which Gemini model is Google's featured workhorse built for long-horizon coding and autonomous agents, released September 2, 2026?

Gemini 1.0 Pro

Gemini 3.8 Flash (gemini-3.8-flash)

Gemma 2B

PaLM 2