Free Generative AI Courses by Google

Enroll in these free generative AI courses by Google and become an expert

Generative AI is a type of artificial intelligence that can create new content, such as text, images, audio, and synthetic data, based on large amounts of data and sophisticated algorithms. Generative AI has many potential applications, such as education, entertainment, customer service, and research. However, it has risks and challenges, such as ethical, social, and security issues.

If you want to learn more about generative AI and how to use it responsibly and effectively, Google has launched a free set of generative AI courses that you can access online. These courses will take you on an exciting journey from the fundamentals of large language models (LLMs) to creating and deploying generative AI solutions on the Google Cloud platform. The courses are designed for learners of different levels and backgrounds, from beginners to experts, developers to business leaders. You can learn quickly and earn badges to showcase your skills and knowledge. The courses are interactive and engaging, with videos, articles, labs, and quizzes.

 Here are the 9 free generative AI courses by Google:

Introduction to Generative AI

This course will give you an overview of generative AI and how it differs from traditional machine learning methods. You will learn about the types and applications of generative AI, as well as the benefits and challenges of using it.

Introduction to Large Language Models (LLMs)

This course will introduce you to LLMs, powerful generative AI models that can classify and generate text, answer questions, and summarize documents. You will learn about the architecture and components of LLMs and how to use prompt tuning to customize their outputs.

Introduction to Responsible AI

This course will teach you about the ethical and social implications of using generative AI and other forms of AI. You will learn about the principles and practices of responsible AI, such as fairness, privacy, accountability, and transparency. You will also learn how to use tools and frameworks to assess and mitigate the risks of using AI.

Introduction to Image Generation

This course will explore how generative AI can create realistic and diverse images based on data and models. You will learn about the types and techniques of image generation, such as variational autoencoders (VAEs) and generative adversarial networks (GANs). You will also learn how to use image generation for various purposes, such as data augmentation, style transfer, and face synthesis.

Encoder-Decoder Architecture

This course will explain how encoder-decoder architecture works in generative AI models. You will learn about the roles and functions of encoders and decoders, as well as how they communicate with each other through latent spaces. You will also learn how to use encoder-decoder architecture for tasks such as image captioning, machine translation, and text summarization.

Attention Mechanism

This course will describe how the attention mechanism works in generative AI models. You will learn about the concept and types of attention mechanisms, such as self-attention and cross-attention. You will also understand how attention mechanisms can improve the performance and efficiency of generative AI models by focusing on relevant information.

Transformer Models and BERT Model

This course will introduce you to the transformer and the BERT models, which are state-of-the-art generative AI models based on attention mechanisms. You will learn about the structure and features of transformer and BERT models and how to use them for various natural language processing tasks, such as sentiment analysis, question answering, and text generation.

Create Image Captioning Models

This course will show you how to create image captioning models using encoder-decoder architecture and attention mechanisms. You will learn how to use Google Cloud Vision API to extract features from images, use ChatGPT to generate captions from features and evaluate the quality of captions using metrics such as the BLEU score.

Deploy Generative AI Solutions on Google Cloud

This course will teach you how to deploy generative AI solutions on Google Cloud using tools and services such as Cloud Storage, Cloud Functions, Cloud Run, Cloud Build, Cloud Shell, Cloud SDK, Cloud Console, and Cloud APIs Explorer. You will learn how to create a serverless web application that can generate captions for images uploaded by users.

Generative AI is a fascinating technology that can create new content based on data and algorithms. It has many potential applications but also some risks and challenges. If you want to learn more about generative AI and how to use it responsibly and effectively, you can enroll in the free generative AI courses by Google. These courses will help you gain the skills and knowledge you need to become a generative AI expert.