OpenCourser brand icon
Sign in
We may earn an affiliate commission when you visit our partners.

Getting started with the Vertex AI Gemini 1.5 Pro Model

Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. This lab will provide an introductory, hands-on experience with Generative AI on Google Cloud.

Enroll now

Here's a deal for you

We found an offer that may be relevant to this course.
Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until April 15
Coursera Plus Sale
Get unlimited access to expert-led courses that give you job-ready certificates with instructors from Google, IBM, and more.
Take
25%
off

What's inside

Syllabus

Getting Started with the Vertex AI Gemini 1.5 Pro Model

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a hands-on introduction to Generative AI using Google Cloud's Vertex AI Gemini 1.5 Pro model, which is ideal for those new to the field
Offers practical experience with Generative AI on Google Cloud, which is valuable for professionals looking to implement AI solutions
Designed as a self-paced lab, which allows learners to complete the course at their own speed and convenience

Save this course

Save Getting started with the Vertex AI Gemini 1.5 Pro Model to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Getting started with the Vertex AI Gemini 1.5 Pro Model with these activities:
Review Generative AI Fundamentals
Review the core concepts of Generative AI to build a solid foundation for understanding the Gemini 1.5 Pro model.
Browse courses on Generative AI
Show steps
  • Read articles and blog posts on Generative AI.
  • Watch introductory videos on LLMs.
  • Complete a basic online course on AI fundamentals.
Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow
Read this book to gain a deeper understanding of the machine learning principles behind the Gemini 1.5 Pro model.
View Hands-On Machine Learning with Scikit-Learn,... on Amazon
Show steps
  • Read the chapters on neural networks and deep learning.
  • Experiment with the code examples provided in the book.
Explore Vertex AI Documentation
Familiarize yourself with the Vertex AI platform by working through the official Google Cloud documentation and tutorials.
Show steps
  • Navigate the Vertex AI documentation website.
  • Follow a tutorial on deploying a simple model.
  • Experiment with different Vertex AI features.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Generative AI with Python and TensorFlow
Study this book to learn more about the specific techniques used in Generative AI models like Gemini 1.5 Pro.
View Generative AI with Python and TensorFlow 2:... on Amazon
Show steps
  • Read the chapters on GANs and VAEs.
  • Implement the code examples provided in the book.
Document Your Gemini 1.5 Pro Experiments
Create a blog post or documentation outlining your experiences and findings while experimenting with the Gemini 1.5 Pro model.
Show steps
  • Choose a topic related to your experiments.
  • Write a clear and concise explanation of your process.
  • Share your documentation with the community.
Experiment with Prompt Engineering
Practice crafting effective prompts for the Gemini 1.5 Pro model to achieve desired outputs and explore its capabilities.
Show steps
  • Research prompt engineering techniques.
  • Test different prompts with the Gemini 1.5 Pro model.
  • Analyze the model's responses and refine your prompts.
Build a Simple Application with Gemini 1.5 Pro
Develop a small application that leverages the Gemini 1.5 Pro model to solve a specific problem or create a novel experience.
Show steps
  • Define the scope and functionality of your application.
  • Design the user interface and data flow.
  • Implement the application using the Gemini 1.5 Pro API.
  • Test and refine your application.

Career center

Learners who complete Getting started with the Vertex AI Gemini 1.5 Pro Model will develop knowledge and skills that may be useful to these careers:
Generative AI Specialist
A Generative AI Specialist focuses specifically on generative artificial intelligence, and this course provides an introduction to the field. The course provides hands-on experience with Google Cloud's Vertex AI, a cloud platform that is highly relevant to generative AI work. Therefore, this course may be particularly useful for a Generative AI Specialist given the focus on this technology in the lab. The skills obtained in this course help build expertise in generative AI development and deployment.
See salaries and explore the career path for Generative AI Specialist
AI Developer
An AI Developer designs, develops, and implements AI applications. This position utilizes knowledge of generative AI and cloud computing, and this course introduces both. The course is useful for an AI Developer, since it provides practical experience with Google Cloud's Vertex AI, a tool common to current AI development. Therefore, this course will help someone in this role use cloud services effectively. Taking this lab will help build a foundation in generative AI model deployment.
See salaries and explore the career path for AI Developer
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This role requires knowledge of generative AI and cloud platforms, both of which are addressed by this course. This course provides you with hands-on experience utilizing Google Cloud's Vertex AI platform, which is directly applicable to the tasks of a Machine Learning Engineer. Therefore, this course may be useful for those interested in working with machine learning models in a cloud environment. The skills gained will build a foundation for understanding how to develop and deploy models for use in real-world applications.
See salaries and explore the career path for Machine Learning Engineer
Cloud Solutions Architect
A Cloud Solutions Architect designs and implements cloud computing solutions. This position requires knowledge of cloud platforms and services, including knowledge of AI and machine learning tools. The hands-on work in this course with Google Cloud's Vertex AI platform may be beneficial to a Cloud Solutions Architect. Therefore, the course provides practical experience in using cloud-based AI services. This course helps build a foundation of knowledge for anyone working in a cloud environment.
See salaries and explore the career path for Cloud Solutions Architect
Cloud Consultant
A Cloud Consultant advises organizations on cloud computing strategies and implementations. This position requires deep knowledge of cloud platforms and services, including artificial intelligence. The kind of practical, hands-on experience with Google Cloud's Vertex AI platform offered in this course may be useful for a Cloud Consultant. Therefore, this course introduces working with generative AI in a cloud environment. This lab can help build a foundation for developing sound cloud strategies that incorporate AI.
See salaries and explore the career path for Cloud Consultant
Data Scientist
A Data Scientist analyzes data and develops models to extract insights. The work of a Data Scientist includes working with machine learning models on cloud platforms, and this course will help with that. The practical, hands-on experience with Google Cloud's Vertex AI platform is directly applicable to data science workflows. Therefore, this course may be useful for a Data Scientist. The skills and knowledge gained from this experience helps build an understanding of cloud-based machine learning.
See salaries and explore the career path for Data Scientist
Research Scientist
A Research Scientist conducts scientific studies and experiments and may utilize machine learning for analysis, often using cloud resources. This course provides hands-on experience with Google's Vertex AI platform. This experience is useful for a Research Scientist who might need to deploy AI models in a cloud environment. This course may be useful to those using cloud based generative AI. The hands-on skills developed in the lab help build an understanding of AI deployment.
See salaries and explore the career path for Research Scientist
Software Engineer
A Software Engineer develops and maintains software systems, and this job may require knowledge of cloud technologies. This course is useful for a Software Engineer as it provides experience with Google Cloud's Vertex AI. This course focuses on generative AI in a hands-on lab, and will likely help anyone who encounters cloud-based AI in their work. The skills from this lab help build experience with cloud tools.
See salaries and explore the career path for Software Engineer
Data Analyst
A Data Analyst examines data to identify trends and insights. Although this role does not build models, it may use machine learning tools, particularly in the cloud. This course may be useful to a Data Analyst as it provides hands-on experience with Google Cloud's Vertex AI platform. Therefore, it provides practical skills for working with cloud-based machine learning technologies. This course will help build a foundational knowledge of working with AI in the cloud.
See salaries and explore the career path for Data Analyst
AI Product Manager
An AI Product Manager directs the development of AI products. They need to understand the technical capabilities of AI models, and this course may help them with this. The practical experience with Google Cloud's Vertex AI platform should be useful for an AI Product Manager needing to understand the technology their products utilize. The hands-on experience of this course may help build a practical understanding of AI models and tools.
See salaries and explore the career path for AI Product Manager
Technology Consultant
A Technology Consultant advises clients on technology solutions, including those involving cloud and AI. This role can benefit from experience with real-world applications. This course provides hands-on experience with Google Cloud's Vertex AI platform. Therefore, it may be useful to a Technology Consultant who wishes to understand the possibilities and limitations of this technology. This course may be relevant to build a foundation in AI technologies deployed in the cloud.
See salaries and explore the career path for Technology Consultant
Business Intelligence Analyst
A Business Intelligence Analyst uses data analysis to inform business decisions. Although this job does not develop models, they may encounter AI tools. This course will help by providing a hands-on experience with Google Cloud's Vertex AI. Therefore, this may help a Business Intelligence Analyst understand AI within the cloud environment. The skills gained during the lab will help anyone build an understanding of cloud-based machine learning.
See salaries and explore the career path for Business Intelligence Analyst
AI Ethics Officer
An AI Ethics Officer develops and enforces ethical practices for AI implementation. This role requires a solid understanding of AI capabilities and limitations, which this course may help to build. This course offers practical experience with Google Cloud's Vertex AI platform, which would be beneficial to an AI Ethics Officer seeking a better understanding of the technology. The course may be useful to build a practical understanding of AI tools.
See salaries and explore the career path for AI Ethics Officer
Quantitative Analyst
A Quantitative Analyst develops mathematical and statistical models. This role often uses cloud platforms. This course, which provides hands on experience with Google's Vertex AI model, may be of use to a Quant. Someone who works with models, and particularly those deployed in the cloud, may gain a more complete understanding of the topic by taking this course. The skills gained help build an understanding of both cloud tools and machine learning models.
See salaries and explore the career path for Quantitative Analyst
Technical Project Manager
A Technical Project Manager oversees technical projects. This position requires at least an understanding of the project's technology, such as machine learning on cloud platforms. This course provides first-hand experience with Google Cloud's Vertex AI. Therefore, an experience like this can help a Technical Project Manager better understand project goals. This experience helps build better communication with tech teams.
See salaries and explore the career path for Technical Project Manager

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Getting started with the Vertex AI Gemini 1.5 Pro Model.
Cover image
Generative AI with Python and TensorFlow 2
Save
Focuses specifically on Generative AI techniques using Python and TensorFlow. It covers various generative models, including GANs and VAEs, which are relevant to understanding the architecture and capabilities of models like Gemini 1.5 Pro. This book provides practical examples and code snippets to help you implement and experiment with generative models. It valuable resource for those looking to delve deeper into the technical aspects of Generative AI.
Generative AI with Python and TensorFlow 2: Create...
Paperback
$$
Generative AI with Python and TensorFlow 2: Create...
Kindle Edition
$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a comprehensive introduction to machine learning concepts and tools, including TensorFlow and Keras. While not specific to Generative AI, it offers a strong foundation in the underlying technologies used in the Gemini 1.5 Pro model. It is particularly helpful for those with limited prior experience in machine learning. This book is commonly used as a textbook at academic institutions.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$

Share

Help others find this course page by sharing it with your friends and followers:
Facebook
LinkedIn
Reddit
X
Link
Email

Similar courses

Similar courses are unavailable at this time. Please try again later.
Effort
1 hour 30 minutes
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Session
January 27, 2025 - February 10, 2025
Language
English
Good to know
Provides a hands-on introduction to Generative AI using Google Cloud's Vertex AI Gemini 1.5 Pro model, which is ideal for those new to the field
Offers practical experience with Generative AI on Google Cloud, which is valuable for professionals looking to implement AI solutions
Designed as a self-paced lab, which allows learners to complete the course at their own speed and convenience
Share and help others discover this course.
Facebook LinkedIn X Reddit Link Email
Don't miss out
Enroll today to gain access to this course
Enroll in this course
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser