Google Free Intro Generative AI Course

 Google Just Released a FREE introductory Generative AI Course 

Here’s everything you need to know about Google’s generative AI learning path.

Via The PyCoach  Artificial Corner,  fromThe PyCoach:   https://artificialcorner.com/ Will review.

A few days ago Google launched a Generative AI learning path with courses that cover topics such as Introduction to Generative AI, Large Language Models, Image Generation, etc.

The best thing is that some of the courses don’t have any prerequisites and are free, so even those with no programming knowledge can make the most of the courses.

https://www.cloudskillsboost.google/journeys/118

Here’s everything you need to know about these AI courses.

Who is this course for?

Anyone who is interested in learning about Generative AI products, Large Language Models, and how to deploy Generative AI solutions should enroll in this course.  ..... 

More background in course.:

That said, among the 10 courses offered by Google there are around 5 courses that require some knowledge in Python and Machine Learning. But, don’t worry, in the next section, I’ll talk more about each course and mention which courses don’t have any prerequisites.

What does Google’s Generative AI learning path cover?

The Generative AI learning path created by Google guides you through a curated collection of content on generative AI products and technologies.

The 5 courses below don’t have any prerequisites.

Introduction to Generative AI: Explains what Generative AI is, how it’s used, and how it differs from traditional machine learning methods.

Introduction to Large Language Models (LLMs): Explains what LLMs are, use cases, and prompt engineering on LLMs.

Introduction to Responsible AI: Explains what responsible AI is, why it’s important, and how Google implements responsible AI in its products.

Introduction to Generative AI Studio: Teaches you what Generative AI Studio is, its features and options, and how to use it.

On the other hand, the rest of the courses require knowledge of Python programming, Machine learning, and Deep learning.

Introduction to Image Generation: Introduces you to the theory behind diffusion models, and how to train and deploy them on Vertex AI.

Encoder-Decoder Architecture: Explains the main components of the encoder-decoder architecture and how to train and serve these models.

Attention Mechanism: Teaches how attention works and how it can improve the performance of different machine learning tasks such as translations, summarization, and question answering.

Transformer Models and BERT Model: Explains the main components of the transformer architecture and how it’s used to build the BERT model.

Create Image Captioning Models: Teaches you how to create an image captioning model by using deep learning.

How to join the course   https://www.cloudskillsboost.google/journeys/118