GenAI on Google Cloud: 4 New Learning Paths to Explore

Level up Your Google Cloud GenAI skills

By Margaret Maynard-Reid, ML GDE & Google Cloud Champion Innovator

Interested in getting started to learning generative AI (GenAI), or level up your GenAI skills? Have you heard of Google Cloud Skills Boost? It’s a learning platform that offers a variety of content to help you upskill in Google Cloud technologies. It provides resources for all skill levels, from beginners to experts.

The content on the platform is organized into learning paths, with each path consisting of a number of courses. You learn from video lectures and hands-on labs in a simulated Google Cloud environment.

Last year Google Cloud launched one generative AI learning path on Google Cloud Skills Boost. Earlier this year the generative AI content was split into two paths: Beginner and Advanced with many new courses added. Then at Cloud Next, an Intermedia Gemini learning path was introduced, with courses on Gemini.

Today Google Cloud announced four new learning paths! Read the official announcement blog post for details. I’m super excited to see that the previous learning paths (beginner, intermediate & advanced) are now well organized to target different audience: app developers, ML engineers, data scientists and data analysts etc. In addition, there are a few new courses introduced along with these new learning paths.

4 New GenAI Learning Path on Google Cloud Skills Boost, Image by Author

So let’s take a look at these four new learning paths!

Generate Smarter GenAI Outputs

This learning path: Generate smarter generative AI outputs, is for app developers who want to build applications with generative AI. It starts with an intro to AI/ML on Google Cloud, then teaches you how to use diffusion models for image generation. It covers how to build a search application with Vector Search and embeddings. Then, it dive deeper into multimodal prompts and multimodal RAG with Gemini to generate text and visual data.

Courses included in this learning path:

1. Intro to AI/ML on Google Cloud
2. Intro to Image Generation
3. Vector Search and Embeddings
4. Build LangChain Apps Using Vertex AI
5. Inspect Rich Documents with Gemini and RAG

Build & Modernize Apps with GenAI

This learning path: Build and modernize applications with generative AI, is for app developers who want to enhance their projects with the power of generative AI. From understanding the core concepts of Gemini, Google’s advanced language model, to building end-to-end applications on Google Cloud, this path will guide you through essential techniques and tools to seamlessly integrate gen AI capabilities into your development workflow. Finally, dive into a hands-on lab to learn how to build your own gen AI applications with Gemini and Streamlit.

Courses included in this learning path:

1. Gemini for App Developers
2. Gemini for End-to-End SDLC
3. Create Generative AI Applications on Google CLoud
4. Website Modernization with Genrative AI on Google CLoud
5. Build Generative AI Agents with Vertex AI & Flutter
6. Develop Generative AI Apps with Gemini and Streamlit

Integrate GenAI into Your Data Flow

This learning path: Integrate generative AI into your data workflow is for data scientists or analysts who want to integrate generative AI into their workflow. It very much focuses on Big Query: learn how to use BigQuery Machine Learning for inference, work directly with Gemini models in BigQuery, and boost your productivity with Gemini’s assistance. Finally, test your knowledge by creating machine learning models with BigQuery ML in a hands-on lab.

Courses included in this learning path:

1. Genimi for Data Scientists and Anlysts
2. Using BigQuery ML for Inference
3. Work with Gemini Models in BigQuery
4. Boost Productivity with Gimini in BigQuery
5. Create ML Model swith BigQuery ML

Deploy & Manage GenAI Models

This learning path: Deploy and manage generative AI models is for ML engineers. It provides a comprehensive introduction to machine learning operations (MLOps), with a specific focus on generative AI. You’ll learn to manage the entire lifecycle of generative AI models, from development and deployment to monitoring. Test your knowledge with a hands-on lab where you’ll train and deploy a model in the cloud with Vertex AI. It also has a few courses on responsible AI.

Courses included in this learning path:

1. MLOps for Generative AI
2. MLOps with Vertex AI: Model Evaluation
3. Responsible AI: Fairness and Bias
4. Responsible AI: Interpretability and Transparency
5. Responsible AI: Privacy and Safety
6. Intro to Security in the World of AI
7. Build and Deploy ML Solutions on Vertex AI

What’s next?

Check out the generative AI learning paths on Google Cloud Skills Boost, and start learning! I hope you find them useful as I do!

Google Cloud Skills Boost offers a variety of courses and learning paths to help you level up your Generative AI skill and beyond. It has many other offerings, for example: Machine Learning Engineer Learning Path, if you would like to get certified Google Cloud MLE. Whether you are a beginner or an expert, you will find these Google Cloud learning paths that help move your career forward.