Last updated: 11 October 2026 (program page, syllabus, projects and prices re-checked on Udacity that day). Written by Josh Hutcheson, OnlineCourseing editor. See our review methodology.
Some links on this page are affiliate links: if you enroll through them we may earn a commission at no extra cost to you. It does not change our verdict, and several of the alternatives we name pay us nothing.
QUICK VERDICT
Our rating: 4.2 / 5
- Best for: Python developers who build on Google Cloud and want four reviewed projects in Gemini, the Agent Development Kit (ADK), Vertex AI Search and the A2A protocol.
- Not for: Developers on AWS or Azure, anyone who wants framework-neutral skills, and beginners without API and prompting experience.
Bottom line: A well-structured 55-hour program that covers ADK more completely than Google’s free materials, with a project at the end of every course. Two cautions: only four learners have rated it so far, and the page does not say who pays for the Google Cloud usage your projects create.
See the Google Agentic AI syllabus →
Google Agentic AI Engineer at a Glance
Coursera Plus, Udemy, or MasterClass?
Get the free 2026 Platform Comparison Guide — 12 platforms compared on price, certificates, and refund policies. Instant PDF, plus my honest Tuesday verdicts.
No spam. Unsubscribe anytime.
| Detail | What Udacity lists (11 October 2026) |
|---|---|
| Program | Google Agentic AI Engineer Nanodegree (nd906) |
| Level | Intermediate |
| Length | 55 hours: 4 courses, 64 lessons, 4 projects |
| Learner rating | 4.5 from 4 reviews |
| Last updated | 6 July 2026 |
| Prerequisites | API fluency, generative AI fluency, basic Python, basic prompting |
| Main tools | Gemini on Vertex AI, Google ADK, Vertex AI Search, Vertex AI Agent Engine, MCP Database Toolbox, A2A, OpenTelemetry |
| Instructors | Brian Cruz, Noble Ackerson, Peter Kowalchuk, Henrique Santana, Allen Firstenberg, Joshua Bernhard, Christopher Agostino |
| Price | $249/month, $846 for 4 months, or $999 one-time (40% off for new members on 11 October) |
What Is the Google Agentic AI Engineer Nanodegree?
It is Udacity’s agentic AI program built on Google Cloud. You start by prompting Gemini through Vertex AI, then build agent workflows in Google’s Agent Development Kit, connect those agents to tools, databases, web search and retrieval, and finish by splitting a multi-agent system into separate services that talk over the Agent2Agent (A2A) protocol.
Udacity sells four agentic programs that teach overlapping ideas on different stacks. The base Agentic AI Nanodegree is framework-agnostic, the LangChain and LangGraph version is the shortest, the Microsoft version uses Microsoft Foundry and Azure, and this one uses Google’s tools. The useful question is which stack you will use at work.
One thing the name may suggest that the page does not support: the program page lists no Google partnership. The instructors are engineers and data scientists from Dell, Leidos, Marketplace and other companies, plus Brian Cruz, who heads AI engineering. The certificate is a Udacity Nanodegree certificate, not a Google Cloud certification.
Curriculum: The Four Courses and Projects
The outline below comes from the program page on 11 October 2026. Hours are Udacity’s estimates.
| Course | Hours | Project you build |
|---|---|---|
| 1. Prompting for Effective LLM Reasoning with Gemini | 12 | Legal Intelligence AI System |
| 2. Agentic Workflows with Google ADK | 15 | AI Research Assistant |
| 3. Building Agents with Google ADK and Vertex AI | 14.5 | Betty’s Bird Boutique customer service agent |
| 4. Multi-Agent Systems with Google ADK and Vertex AI | 14 | Multi-Agent Banking System |
Course 1: Prompting for Effective LLM Reasoning with Gemini (12 hours)
Each technique comes as a theory lesson followed by an implementation lesson in Vertex AI Gemini: role-based prompting, chain-of-thought and ReAct prompting, systematic prompt refinement, prompt chaining with validation between steps, and feedback loops for code generation with retries and quality gates. The project asks for an agent that produces consistent business intelligence reports with built-in quality checks and reasoning traces an analyst can review.
Course 2: Agentic Workflows with Google ADK (15 hours)
This course introduces ADK and works through the standard workflow patterns one at a time: prompt chaining, routing, parallelization with fan-out and fan-in, evaluator-optimizer loops with generator and critic agents, and orchestrator-worker designs. You model each workflow before coding it, then handle state, errors and execution analysis. The project is an AI Research Assistant that routes a query to specialized agents, runs work in parallel and writes a report.
Course 3: Building Agents with Google ADK and Vertex AI (14.5 hours)
The longest list of skills sits here. You add tools to agents, force structured outputs with Pydantic, manage agent state, and build short-term memory and then long-term memory with ADK’s MemoryService and Vertex AI Agent Engine. You call external APIs with keys stored in Google Cloud Secret Manager, ground web-search answers with Google Search, query databases through the MCP Database Toolbox, and build single-agent retrieval (RAG) on Vertex AI Search. The course closes with agent evaluation and with tracing through OpenTelemetry and Google Cloud Trace. The project is a customer service agent for a fictional bird shop that answers from databases, files and the web while refusing orders and off-topic requests.
Course 4: Multi-Agent Systems with Google ADK and Vertex AI (14 hours)
You design multi-agent architectures, document agent capabilities as A2A Agent Cards, and implement orchestrators that delegate to specialized sub-agents. ADK’s SequentialAgent and ParallelAgent handle ordered and concurrent work, and a CustomAgent applies deterministic business rules where you do not want a model deciding. Later lessons cover explicit session state across turns, distributed agents that call each other through RemoteA2aAgent with shared MySQL state, and multi-agent RAG that combines Vertex AI Search with SQL. The project is a banking prototype in which separate agents handle deposits, loans and account information and share only limited data over A2A.
See the full Google Agentic AI outline →
What You Finish With
Four reviewed projects, one per course, each built on the same Google stack:
- A report-writing agent that uses chain-of-thought, prompt chains and feedback loops, with reasoning traces a person can audit.
- A multi-agent research assistant that routes questions and runs parallel workflows in ADK.
- A customer service agent with tools, memory, database access through MCP, grounded web search, retrieval and tracing.
- A distributed banking system whose agents are separate services that discover and call each other over A2A.
For a portfolio, the last two matter most. They show the parts of agent work that tutorials tend to skip: what the agent is allowed to refuse, where state lives, how calls are traced, and how separate services agree on what each one does.
Who Teaches It
Udacity lists seven instructors: Brian Cruz (head of AI engineering), Noble Ackerson (senior director of AI and agentic solutions at Leidos), Peter Kowalchuk, Henrique Santana (principal machine learning engineer at Dell Technologies), Allen Firstenberg, Joshua Bernhard (staff data scientist at Marketplace) and Christopher Agostino (founder of NPC Worldwide). Three of them also teach the LangChain program, which is why the course structures look alike.
Google Agentic AI vs Udacity’s Other Agentic Programs
The four programs share a pattern (prompting, workflows, single agents, multi-agent systems) and differ mainly in the stack. Figures are from each program page in October 2026.
| Program | Udacity estimate | Structure | Main stack | Learner rating |
|---|---|---|---|---|
| Agentic AI (nd900) | 53 hours | 4 courses, 4 projects | Framework-agnostic agent patterns | 4.8 (581 reviews) |
| Agentic AI with LangChain and LangGraph (nd901) | 26 hours | 3 courses, 3 projects | LangChain, LangGraph, MLflow, RAGAS | 4.7 (21 reviews) |
| Microsoft Agentic AI (nd904) | 56 hours | 4 courses, 4 projects | Microsoft Foundry and Azure | 5.0 (1 review) |
| Google Agentic AI Engineer (nd906) (this review) | 55 hours | 4 courses, 4 projects | Gemini, Google ADK, Vertex AI, A2A | 4.5 (4 reviews) |
Choose by employer stack. If your company runs on Google Cloud, this program teaches the services you will use, including Vertex AI Search and Agent Engine, which the other programs do not cover. If you want the shortest route to a working agent in open-source tools, the LangChain program covers similar ground in about half the hours. If you do not know your stack yet, the base Agentic AI program has by far the most learner reviews (581) and teaches the patterns without a vendor attached.
How Much Does the Google Agentic AI Engineer Nanodegree Cost?
Udacity sells its Nanodegrees as part of a subscription to the whole catalog, and for some programs as a one-time purchase. These are the prices on the Google Agentic AI Engineer Nanodegree page on 11 October 2026:
| Plan | List price | Today (50% off) | What you get |
|---|---|---|---|
| Monthly subscription | $249 / month | $125 / month | The whole Udacity catalog; cancel anytime |
| 4-month bundle | $846 ($212 / month) | $423 for 4 months | The 15% bundle discount covers the first 4 months, then the plan rolls to month-to-month |
| Buy just this program | $999 one-time | $499.50 one-time | The Google Agentic AI Engineer Nanodegree only |
On 11 October Udacity was advertising 40% off any plan for new members, and the discounted figures above are what the program page showed with that offer applied. Our link carries the reader code onlinecourseing40, which is the same 40%. If Udacity is running a bigger sale when you read this, check that your cart shows the larger discount before you pay.
Which plan is cheaper depends on your pace. At today’s 50% off, four months on the bundle cost $423, less than the $499.50 one-time purchase, so the subscription wins if you finish within about four months. The one-time purchase makes sense if you expect to take longer, but it covers this program alone, while the subscription opens every other Nanodegree.
Check the current Google Agentic AI price →
Udacity estimates 55 hours. At 8 to 10 hours a week that is six to seven weeks, so a four-month bundle leaves room for the reviewed projects to come back with revisions. Budget separately for Google Cloud usage, because the program page does not say whether Udacity covers it.
Pros and Cons
Pros
- Covers the Google-specific services. Vertex AI Search for retrieval, Agent Engine for memory, Secret Manager for keys, Cloud Trace for observability and A2A for distributed agents all get hands-on lessons.
- A reviewed project in every course. Four projects that grow in scope, ending in a multi-service system.
- Deterministic control is taught, not skipped. The CustomAgent lessons show how to enforce business rules without leaving them to the model.
- Reasonable length. 55 hours fits inside a four-month bundle for most people with the prerequisites.
Cons
- Only four learner reviews. The 4.5 average is too small a sample to tell you much yet.
- Cloud costs are unclear. The page does not say whether Udacity supplies a Google Cloud project or credits.
- Tied to one cloud. The concepts transfer, but the code does not run unchanged on AWS or Azure.
- Fast-moving tools. ADK and A2A change often. The program was last updated on 6 July 2026, so check lesson code against the current ADK documentation.
- No Google credential. You earn a Udacity Nanodegree certificate. The page names no Google partnership.
Who Should Take It
Take it if your team builds on Google Cloud and is adopting ADK or Vertex AI for agents, you want to understand A2A by building with it, or you are moving into an agent engineering role at a Google Cloud customer and want projects that use the same services.
Skip it if you work on AWS or Azure (look at the Microsoft program or the base Agentic AI program), you want vendor-neutral open-source skills (take the LangChain program), or you have not yet called an LLM API from Python. In that case start with the Generative AI Nanodegree or Google’s own beginner material.
Alternatives
| Option | Format | Cost | Best for |
|---|---|---|---|
| Udacity Agentic AI (nd900) | 53 hours, 4 reviewed projects | Same Udacity plans | Agent patterns without a cloud attached |
| Udacity Agentic AI with LangChain (nd901) | 26 hours, 3 reviewed projects | Same Udacity plans | Open-source tools, shortest path |
| Udacity Microsoft Agentic AI (nd904) | 56 hours, 4 reviewed projects | Same Udacity plans | Teams on Azure and Microsoft Foundry |
| Google ADK documentation | Official docs and tutorials | Free | Self-directed learners who do not need reviewed projects |
| Google Skills | Google’s own learning site | Varies by course | Google Cloud training and credentials beyond agents |
If you only want to learn ADK and can direct yourself, Google’s documentation and the A2A specification are free and current. The Nanodegree adds structure, project review and a single sequence through the services. For the wider Google Cloud credential path, see our Google Cloud certification guide.
WHAT WE CORRECTED IN THIS UPDATE
An earlier version of this review, written in April 2026, said things the program page does not support. We re-read the page and its syllabus data on 11 October 2026 and fixed the following:
- It called the program “co-branded” and “co-developed” with Google. The program page names no partner.
- It described a single capstone. Every course ends in its own reviewed project, four in total.
- It said the Gemini course exploits Gemini’s large context window and multimodal input. The course teaches prompting patterns (roles, chain-of-thought, ReAct, refinement, chaining, feedback loops), not those features.
- It called the seven-instructor list the largest of any agentic program. We could not verify that and removed it.
- It gave the bundle as $848. The page shows $846.
Frequently Asked Questions
Is the Udacity Google Agentic AI Engineer Nanodegree worth it?
It is worth it if you build on Google Cloud and want reviewed projects in Google’s Agent Development Kit, Vertex AI and the A2A protocol. At the 40% new-member rate, four months cost $507.60, and Udacity estimates 55 hours, so most people with the prerequisites can finish inside that window. It is a weaker buy if you do not work on Google Cloud: the framework-agnostic Agentic AI Nanodegree or the LangChain version teaches skills that move between clouds more easily.
How long does the Google Agentic AI Engineer Nanodegree take?
Udacity estimates 55 hours across four courses: about 12 hours for Gemini prompting, 15 for ADK workflows, 14.5 for building agents with ADK and Vertex AI, and 14 for multi-agent systems. At 10 hours a week that is roughly six weeks.
What is Google’s Agent Development Kit (ADK)?
ADK is Google’s open framework for building AI agents in code. It provides agent types for sequential, parallel and loop workflows, tool calling, session state, memory and evaluation, and it deploys to Vertex AI Agent Engine. Google publishes the documentation at adk.dev. The Nanodegree uses ADK in all three courses after the first.
What is the Agent2Agent (A2A) protocol?
A2A is an open protocol for agents built by different teams or on different frameworks to discover each other and exchange tasks. An agent publishes an Agent Card describing what it can do, and other agents call it over the network. In the final course you use ADK’s RemoteA2aAgent and Agent Cards to split a banking assistant into separate services.
Do I need Google Cloud experience for this Nanodegree?
Udacity does not list Google Cloud as a prerequisite. The listed prerequisites are API fluency, generative AI fluency, basic Python and basic prompting. Each course starts with a lesson on setting up Google Cloud resources, so expect to work in a Google Cloud project from the first week.
Does Udacity pay for the Google Cloud usage?
The program page does not say. Its outline has you set up Google Cloud resources at the start of each course, but it does not state whether Udacity provides a project or credits. If you would be paying your own cloud bill, ask Udacity before you enroll and set a budget alert in Google Cloud.
Is this program made by Google?
The program page does not name Google as a partner. It is a Udacity Nanodegree taught by seven Udacity instructors from industry, built around Google’s tools. Treat the name as a description of the stack rather than a Google credential.
How is it different from the base Agentic AI Nanodegree?
The base program (nd900, 53 hours) teaches agent patterns without tying you to one cloud. This program teaches the same ideas through Google’s stack: Gemini on Vertex AI, ADK, Vertex AI Search, Agent Engine memory and A2A. Pick the base program if your employer’s stack is undecided, this one if it is Google Cloud.
Related reading: Udacity Agentic AI Nanodegree review · LangChain and LangGraph Nanodegree review · Microsoft Agentic AI review · Is a Udacity Nanodegree worth it? · Best AI certifications · Every Udacity program we review