Introduction to AI and Machine Learning on Google Cloud
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Introduction to AI and Machine Learning on Google Cloud
This course is part of multiple programs.
Instructor: Google Cloud Training
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What you'll learn
Recognize the data-to-AI technologies and tools offered by Google Cloud.
Use generative AI capabilities in applications.
Choose between different options to develop an AI project on Google Cloud.
Build ML models end-to-end by using Vertex AI.
Skills you'll gain
- MLOps (Machine Learning Operations)
- Machine Learning Methods
- Cloud Infrastructure
- Natural Language Processing
- Model Training
- Large Language Modeling
- Generative AI Agents
- Artificial Intelligence and Machine Learning (AI/ML)
- Artificial Intelligence
- Agentic systems
- Generative Model Architectures
- Applied Machine Learning
- Google Cloud Platform
- Prompt Engineering Tools
Details to know
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 6 modules in this course
This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions. It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project based on the different goals of users, including data scientists, AI developers, and ML engineers.
This lesson guides learners through the course structure, which is built upon a three-layer AI framework: AI infrastructure, development, and solutions. It outlines the learning objectives and introduces learners to Google's comprehensive suite of full-stack AI development tools.
What's included
1 video
1 video•Total 4 minutes
- Course introduction•4 minutes
This module begins with a use case demonstrating the AI capabilities. It then focuses on the AI infrastructure like compute and storage. It also explains the primary data and AI development products on Google Cloud. Finally, it demonstrates how to use BigQuery ML to build an ML model, which helps transition from data to AI.
What's included
6 videos1 reading1 assignment1 app item1 plugin
6 videos•Total 32 minutes
- A use case•6 minutes
- AI on Google Cloud•5 minutes
- AI infrastructure•7 minutes
- AI models•6 minutes
- BigQuery ML•6 minutes
- Summary•3 minutes
1 reading•Total 10 minutes
- Reading•10 minutes
1 assignment•Total 30 minutes
- Quiz.•30 minutes
1 app item•Total 60 minutes
- Lab: Predict Visitor Purchases with BigQuery ML•60 minutes
1 plugin•Total 15 minutes
- Accessing and completing labs•15 minutes
This module introduces generative AI (gen AI), the latest AI advancement, and the Google Cloud toolkits for developing gen AI projects. It starts by examining the foundation models. It then investigates the prompt-to-production lifecycle with Vertex AI Studio, including prompt engineering, app deployment, and model tuning. Additionally, this module explores AI agents and Google’s full stack of AI agent development tools.
What's included
8 videos1 reading1 assignment1 app item
8 videos•Total 57 minutes
- Generative AI on Google Cloud•4 minutes
- Foundation models•8 minutes
- Idea to app•10 minutes
- Prompt engineering•8 minutes
- Deployment and model tuning •8 minutes
- AI agents•7 minutes
- Agent building with Google Cloud•9 minutes
- Summary•3 minutes
1 reading•Total 10 minutes
- Reading List•10 minutes
1 assignment•Total 10 minutes
- Quiz.•10 minutes
1 app item•Total 60 minutes
- Lab: Get started with Vertex AI Studio•60 minutes
This module explores the various options for developing an AI project on Google Cloud, from ready-made solutions like pre-trained APIs, to no-code and low-code solutions like AutoML, and code-based solutions like custom training. It compares the advantages and disadvantages of each option to help decide the right development tools.
What's included
7 videos1 reading1 assignment1 app item
7 videos•Total 30 minutes
- AI developement options•5 minutes
- Vertex AI•4 minutes
- AutoML•5 minutes
- Pre-trained APIs•4 minutes
- Custom training•6 minutes
- Lab introduction•5 minutes
- Summary•1 minute
1 reading•Total 10 minutes
- Reading•10 minutes
1 assignment•Total 12 minutes
- Quiz.•12 minutes
1 app item•Total 45 minutes
- Lab: Entity and sentiment analysis with natural language API•45 minutes
This module walks through the ML workflow from data preparation, to model development, and to model serving on Vertex AI. It also illustrates how to convert the workflow into an automated pipeline using Vertex AI Pipelines.
What's included
8 videos1 reading1 assignment1 app item
8 videos•Total 41 minutes
- ML workflow•4 minutes
- Data preparation•3 minutes
- Model development•6 minutes
- Model serving•3 minutes
- MLOps and workflow automation•6 minutes
- Lab introduction (optional)•5 minutes
- How a machine learns (optional)•11 minutes
- Summary•1 minute
1 reading•Total 10 minutes
- Reading•10 minutes
1 assignment•Total 10 minutes
- Quiz.•10 minutes
1 app item•Total 60 minutes
- Lab: Vertex AI: Predicting Loan Risk with AutoML (optional)•60 minutes
This lesson summarizes the course by addressing the most important concepts, tools, technologies, and products for each module.
What's included
1 video2 readings
1 video•Total 9 minutes
- Course summary•9 minutes
2 readings•Total 20 minutes
- Reading•10 minutes
- Course resources•10 minutes
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- 5 stars
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- 4 stars
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- 3 stars
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- 2 stars
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- 1 star
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Reviewed on Aug 20, 2025
It's excellent with a lot of excellent additional reading to deep dive. Thanks
Reviewed on Oct 16, 2024
Well-structured for beginners, it balances theory with hands-on exercises. While it could go deeper, it's an excellent springboard for further learning in AI/ML.
Reviewed on Sep 24, 2024
This course is a good intro to cloud computing and IA
Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
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Financial aid available,