Free Generative AI Courses from Google

Google has launched ten new generative AI learning courses to help upskill those looking for jobs in the future.

Google’s new generative AI learning path is now available for free for anyone willing to kick start their career with AI. The learning path covers 10 different courses designed in such a way that even a beginner could get a better understanding of how AI and machine learning work – especially in a world where AI automation will replace jobs.

The courses focus on the differences between AI and machine learning, an introduction to Google’s machine learning training platform Vertex AI and the ethics around responsible AI development.

It’s intended as a jumping-off point for users to understand generative AI, how it fits into the broader AI ecosystem and where they can find other learning materials to help users retrain in new AI-focused careers.

Generative AI Learning Path Course Details:

1. Introduction to Generative AI

An introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. Learn More

2. Introduction to Large Language Models

An introductory level microlearning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Learn More

3. Introduction to Responsible AI

An introductory level microlearning course aimed at explaining what responsible AI is, why it’s important, and how Google implements responsible AI in their products. Learn More

4. Generative AI Fundamentals

When you complete this course, you can earn the badge for “Generative AI Fundamentals”. Which an be added to your profile page. Learn More

5. Introduction to Image Generation

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Learn More

6. Encoder-Decoder Architecture

This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. Learn More

7. Attention Mechanism

This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. Learn More

8. Transformer Models and BERT Model

This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. Learn More

9. Create Image Captioning Models

This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. Learn More

10. Introduction to Generative AI Studio

This course introduces Generative AI Studio, a product on Vertex AI, that helps you prototype and customize generative AI models so you can use their capabilities in your applications. Learn More

Since the launch of OpenAI’s ChatGPT, Google has raced to catch up with its own Bard version for users. Recently it announced there would be significant changes coming to Google’s search function, a core part of the business where it holds the major market share.

Stay Tuned!