Google AI courses in 2026: what each one teaches, costs and certifies

Google AI courses come in two families: no-code courses on using AI at work (Google AI Essentials and the newer Google AI Professional Certificate, both $49 a month on Coursera in the US and Canada), and technical courses for people who want to build with AI (the free Machine Learning Crash Course and the Google Skills catalog, which has free monthly credits and a $29-a-month Pro plan). Much of the learning material is free. Paid certificates and Google Cloud certification exams are where the money goes, and I think that's a fair split.

This guide maps the whole catalog as of late October 2026: what each course teaches, how long it really takes, what it costs and what you walk away with. We built it from Google's own course pages on Grow with Google, Google Skills and Coursera, plus published independent reviews. Nobody at The AI Future took these courses for this article, so I'll say where the numbers come from as we go.

Google AI courses at a glance

If you only read one section, make it this one. Prices are US list prices, checked October 2026.

Google's AI training, organised

Google has three shelves in one shop. It's spent the last year moving everything under one roof, but the shelves still work differently.

Shelf 1: Grow with Google (using AI at work)

Grow with Google is the career-training arm. Its AI courses assume zero technical background and teach you to use tools like Gemini, Gemini Notebook and Gemini in Google Workspace.

The two headline programs, AI Essentials and the AI Professional Certificate, are hosted on Coursera and billed through a Coursera subscription. Going by Google's FAQ, "In the U.S. and Canada, the subscription cost is $49 USD per month after an initial 7-day free trial period" for AI Essentials, and the Professional Certificate page lists the same $49 a month, adding that the certificate is also available on Google Skills and Udemy. Prices may be lower in other countries.

Shelf 2: Google Skills (building with AI)

Google launched Google Skills as a single platform with "nearly 3,000 courses, labs and credentials", combining content from Google Cloud, Google DeepMind, Grow with Google and Google for Education. On the plans page, there are two tiers:

• Starter costs nothing: 35 free credits every month, limited hands-on labs and skill badges at all levels.
• Pro is $29 a month: unlimited hands-on labs from beginner to advanced, with a 7-day trial for new subscribers.

Video courses such as Beginner: Introduction to Generative AI (a four-activity path covering large language models through to responsible AI) are the free on-ramp. Labs, which spin up real Google Cloud projects, are what eat credits (that's the catch with the free tier).

Shelf 3: Free developer material and certifications

The Machine Learning Crash Course on Google for Developers is free and needs no account. It covers linear and logistic regression, classification, data preparation, neural networks, embeddings and, in its refreshed version, a new module on large language models. Above that sit Google Cloud certifications, which are proctored exams with fees, such as the Generative AI Leader ($99) and the Professional Machine Learning Engineer ($200).

If you'd like the theory behind all of this before you pick a course, our explainer on AI, machine learning and deep learning covers how the layers fit together.

Real examples: what each course actually teaches

Google AI Essentials

Five modules: Introduction to AI, Maximize Productivity With AI Tools, Discover the Art of Prompting, Use AI Responsibly, and Stay Ahead of the AI Curve, according to Grow with Google. The exercises are workplace chores: brainstorming an outline, organising research against criteria, drafting email replies. Reliablesoft, which reviewed the program in 2026, reports a 4.8 rating from 25,448 Coursera reviews and 1,996,687 enrolled learners, and calls the prompting module the most valuable part.

Google AI Professional Certificate

This is the bigger sibling. Google lists eight courses: AI Fundamentals, then AI for Brainstorming and Planning, Research and Insights, Writing and Communicating, Content Creation, Data Analysis, App Building and App Deployment. You complete 20+ hands-on activities with Gemini Canvas, Deep Research, Gemini Notebook, Gemini in Sheets and Google AI Studio. The two app courses teach "vibe coding": describing a tool in plain language and letting AI write it. Enrolment includes three months of Google AI Pro.

Google says the curriculum was built with the Burning Glass Institute and checked by a group of 12 large US employers. The Interview Guys, in a review that carries affiliate links, put the certificate at 4.8 out of 5 from over 1,174 Coursera reviews shortly after its February 2026 launch.

Introduction to Generative AI and Introduction to Large Language Models

These are short Google Skills courses: Introduction to Generative AI runs 45 minutes and explains how generative AI differs from traditional machine learning; Introduction to Large Language Models runs one hour and covers use cases and prompt tuning. They're the closest thing Google has to free, badge-earning AI classes online. If you're weighing these against other providers, see our guide to choosing a generative AI course.

Machine Learning Crash Course

This one is a real AI programming course. Google's prerequisites page says "You should be a good programmer", ideally in Python, and expects comfort with algebra, basic statistics and functions such as the sigmoid. Exercises run in Colab notebooks in the browser using NumPy, pandas and Keras.

Advanced: Generative AI for Developers

A 12-activity Google Skills path for app developers, ML engineers and data scientists, with the beginner gen AI path as a recommended prerequisite. Expect labs here, which means credits or a Pro subscription.

5-Day AI Agents Intensive with Kaggle

A free, live cohort. Google says its first run reached over 1.5 million learners, and it ran again on 15 to 19 June 2026 with a vibe-coding focus and a capstone project. It isn't always open, so watch for the next date.

A worked example: what your route will cost

Course prices look simple until you multiply by time. Three common routes follow, using Google's listed prices and lengths.

The arithmetic for the second row: eight courses at roughly an hour each is about 8 hours. At 2 hours a week you finish in four weeks, inside one billing month, so you pay $49 once. Slip to one hour a week and you cross into a second month: $98 for the same certificate. The subscription model rewards a fixed schedule, and punishes procrastination.

For the developer route, the crash course and video courses cost nothing. If you stay within 35 free credits a month on Google Skills, your only cost is the $99 exam. Add two months of Pro at $29 for unlimited labs and the total is $157.

Benefits and limitations

Strengths

• Entry cost is low: the core no-code programs cost $49 a month, and a lot of material (MLCC, educator course, intro gen AI videos) is free.
• The courses are short and practical: the Professional Certificate's courses are about an hour each, and you can pick only the ones relevant to your job.
• Language coverage is wide: Google says the Professional Certificate has been translated into 16 languages beyond English, including Arabic, Japanese, Spanish and Vietnamese.
• There's a clear ladder: beginner badge, entry-level certificate, then a proctored certification, all on one platform.

The limits

• The no-code certificates aren't technical credentials. Google states the Professional Certificate "does not carry university credit". The Interview Guys note that a hiring manager for a machine learning role "will notice the mismatch" if this is your only AI credential.
• There's some tool lock-in. The activities use Gemini, Gemini Notebook, Workspace and AI Studio. Prompting skills transfer to other assistants; the click-paths probably don't.
• Google's own numbers disagree. AI Essentials is "under 5 hours" on Grow with Google and "under 10 hours" on Coursera. The Professional Certificate FAQ gives eight courses in one answer and "all seven courses" in another. Plan for the higher figure; I wouldn't trust the shorter one.
• Credits run out fast. 35 monthly credits on Google Skills cover a few labs, not a full advanced path. Serious hands-on learners end up on Pro.
• Things change quickly. Tools named in the syllabus (Veo, Nano Banana, Gemini Notebook) are renamed or replaced often, which Google acknowledges by saying it updates its AI training to keep it relevant.

Choosing a route

Pick by goal, not by brand. The table below should cover most cases.

Three practical tips.

1. Block your calendar before you start the trial. The 7-day free trial is long enough for AI Essentials only if you schedule the hours up front.
2. Turn the activities into proof. A certificate badge says little on its own, and the Professional Certificate's 20+ activities give you real artefacts, like a cleaned dataset or a small app, to show in interviews.
3. Learn prompting deliberately. It's the skill that transfers best between tools, in my view. Our prompt engineering guide and beginner's guide to Gemini pair well with any Google course.

If you want to compare Google with other providers, our roundup of the best AI courses for beginners and our guide to AI training courses cover options from universities and other platforms. For the career side, see AI jobs in 2026.

The direction of Google's courses

Three trends show up in Google's own pages. First, consolidation: Google Skills is becoming the single front door, with Grow with Google certificates now listed there as well as on Coursera and Udemy. Second, a shift from prompting to building: the newest material is about vibe coding and agents, from the App Deployment course to the Kaggle agents intensive. Third, role-specific spin-offs: Grow with Google already promotes a Google AI for Healthcare Professionals Certificate, built by clinicians at Google, alongside the educator course.

The Google AI Pro bundle has an end date too. Grow with Google says the offer must be redeemed by 1 January 2027, so if the three months of AI Pro matter to you, check the current terms before you enrol.

FAQ

Are Google AI courses free?

Some are. The Machine Learning Crash Course, Generative AI for Educators with Gemini, the Kaggle agents intensive and many Google Skills video courses cost nothing. Google AI Essentials and the AI Professional Certificate cost $49 a month in the US and Canada after a 7-day trial; Reliablesoft notes that Coursera also offers financial aid.

Is there a free Google AI certification?

Not a full one. Free options give you badges (Google Skills) or a course certificate (the educator course). The Google AI Essentials and Professional certificates need a paid Coursera subscription unless you finish within the trial, and Google Cloud certifications such as Generative AI Leader carry a $99 exam fee.

How long does Google AI Essentials take?

Google gives two figures: under 5 hours on Grow with Google and under 10 hours on Coursera. Reliablesoft estimates about 8 hours across five courses. Plan for 8 to 10 hours.

Which is better, AI Essentials or the AI Professional Certificate?

For most people paying $49 anyway, the Professional Certificate covers more: eight courses, 20+ activities and three months of Google AI Pro. AI Essentials suits complete beginners who want the shortest possible introduction. If you already prompt AI tools weekly, go straight to the Professional Certificate.

Do Google AI courses teach coding?

The Grow with Google programs don't; they teach no-code use of AI, including vibe coding apps without writing code. For real programming, use the Machine Learning Crash Course, which expects Python skills, and the developer paths on Google Skills.

Will a Google AI certificate get me a job?

On its own, probably not. It signals AI fluency for roles like marketing, operations or project management, where independent reviewers say it can help you stand out. For technical AI roles, employers look for programming skills, projects and certifications such as Google Cloud's Professional Machine Learning Engineer.