Free Google Cloud Learning Path for Gemini

Introduction to Gemini

It is the era of linguistic models and technology/ai/google-gemini-ai/” rel=”noopener” target=”_blank”>Gemini It's Google's latest and most capable model to date.

Gemini is the result of large-scale collaborative efforts by teams across Google, including our colleagues at Google Research. It was built from the ground up to be multimodal, meaning it can generalize and seamlessly understand, operate on, and combine different types of information, including text, code, audio, image, and video.

If you are interested in learning about Gemini, language models and using them to your advantage, Google has launched a new learning path focused on intermediate language models, the Gemini learning path for Google Cloud. Discover the learning path below.

The path of learning

The Google Cloud Gemini learning path demonstrates how Gemini can be a force multiplier for different roles. Complete with its natural language conversational chat interface, Gemini enables quick interactions for cloud-related questions or provides advice on best practices. Assists with coding tasks by providing code completion or generation as you type or occasionally based on comments made. The learning path can facilitate various roles such as developers, data analysts, cloud engineers, architects, and security engineers.

In the first course, Gemini for App Developers, learn how Gemini can help you build apps. Learn everything about requests, code explanation, and even code generation.

In the second course, Gemini for Cloud Architects, learn how Gemini helps provision infrastructure. See how Gemini can explain infrastructure, upgrade it, and deploy Google Kubernetes Engine clusters. The course uses a hands-on lab to help consolidate learning.

The third course, Gemini for Data Analysts and Scientists, finds that it can help analyze data and make predictions. Focusing on customer data, learn how to identify, categorize, and develop new customers with the help of Google's BigQuery.

The next course, Gemini for Network Engineers, demonstrates how Gemini helps network engineers create and manage virtual private cloud networks. Learn prompting strategies for Gemini to help you with your networking tasks.

The fifth course is titled Gemini for Security Engineers and is designed to show you how to treat Gemini as a collaborator in protecting your cloud environment and resources. You'll see how Gemini can help you deploy example workloads in a Google Cloud environment and identify security misconfigurations.

Course number 6, Gemini for DevOps Engineers, covers how Gemini can help engineers manage their infrastructure. Use Gemini to understand and manage application logs, create Google Kubernetes Engine clusters, and more.

The seventh course, Gemini for End-to-End SDLC, demonstrates using Gemini along with additional Google products and services to develop, test, deploy, and manage your own applications, from startup to deployment.

In the final course of the learning path, Develop GenAI Applications with Gemini and Streamlit, learn all about generating text, using function calls, and creating and deploying a Streamlit application with Cloud Run.

Summary

Learn how to leverage Gemini for a multitude of engineering tasks with Google Cloud's latest learning path, the Gemini learning path for Google Cloud. Check out the more detailed information on a course-by-course basis to see if this is something you might benefit from in your professional life.

Matthew May (twitter.com/mattmayo13″ rel=”noopener”>@mattmayo13) has a master's degree in computer science and a postgraduate diploma in data mining. As Editor-in-Chief, Matthew aims to make complex data science concepts accessible. His professional interests include natural language processing, machine learning algorithms, and exploring emerging ai. He is driven by the mission to democratize knowledge in the data science community. Matthew has been coding since he was 6 years old.