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Introduction to Gemini
It’s the era of language models, and Gemini is 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, which means it can generalize and seamlessly understand, operate across 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 benefit, Google has launched a new intermediate language model-focused learning path, the Gemini for Google Cloud Learning Path. Find out about the learning path below.
The Learning Path
The Google Cloud Gemini Learning Path demonstrates how Gemini can be a force multiplier for a number of different roles. Complete with its conversational natural language chat interface, Gemini enables quick interactions for cloud-related questions or provides advice on best practices. It helps with coding tasks by providing code completions or code generation as you type, or occasionally based on comments made. The learning pathway can facilitate various roles, such as devs, data analysts, cloud engineers, architects, and security engineers.
In the first course, Gemini for Application Developers, learn how Gemini can help you build applications. Learn all about prompting, getting code explained, and even generating code.
In the second course, Gemini for Cloud Architects, find out how Gemini helps to provision infrastructure. See how Gemini can explain infrastructure, update infrastructure, and deploy Google Kubernetes Engine clusters. The course uses a hands-on lab to help cement learning.
The third course, Gemini for Data Scientists and Analysts, discover can help analyze data and make predictions. With a focus 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 to have Gemini assist with your 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 for securing your cloud environment and resources. You will see how Gemini can help deploy example workloads into a Google Cloud environment, and to identify security misconfigurations.
Course number 6, Gemini for DevOps Engineers, covers how Gemini can help engineers manage their infrastructure. Use Gemini for understanding and managing application logs, create a Google Kubernetes Engine clusters, and more.
The seventh course, Gemini for end-to-end SDLC, demonstrates using Gemini alongside additional Google products and services to develop, test, deploy, and manage your own applications, from inception to deployment.
In the final course in the learning path, Develop GenAI Apps with Gemini and Streamlit, learn all about text generation, using function calls, and creating and deploying a Streamlit application with Cloud Run.
Summary
Learn how to leverage Gemini for a whole host of engineering tasks with Google Cloud’s latest learning path, the Gemini for Google Cloud Learning Path. Check out the more detailed information course-by-course to see if this is something that you could benefit from in your professional life.
Matthew Mayo (@mattmayo13) holds a Master’s degree in computer science and a graduate diploma in data mining. As Managing Editor, 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 a mission to democratize knowledge in the data science community. Matthew has been coding since he was 6 years old.
