Google Launches Free AI Courses: Are You Interested in Trying Them Out?
Google has recently launched a series of free AI courses, and the best part is that some of these courses don't require any special prerequisites, making them accessible even to those without programming knowledge. Here's everything you need to know about these Google AI courses.
Who can take these courses?
Anyone interested in learning about Generative AI products, Large Language Models (LLMs), and how to implement Generative AI solutions should consider enrolling in these courses.
Among the 10 courses offered by Google, approximately 5 courses do require basic knowledge of Python and Machine Learning. However, don't worry, in the following sections, we will discuss the details of each course and specify which ones have no specific prerequisites.
Upon completing the courses, you will receive a neat badge like the one shown below.
What does the Generative AI learning path from Google offer?
Google's Generative AI learning path will guide you through a curated collection of content on Generative AI products and technologies.
The following are some courses that do not have specific prerequisites:
- Introduction to Generative AI: Explains what Generative AI is, its applications, and how it differs from traditional machine learning methods.
- Introduction to Large Language Models (LLMs): Explains what LLMs are, their use cases, and techniques for working with LLMs.
- Introduction to Responsible AI: Explores the concept of Responsible AI, why it is important, and how Google implements Responsible AI in its products.
- Introduction to Generative AI Studio: Teaches what Generative AI Studio is, its features and options, and how to use it.
On the other hand, the remaining courses require knowledge of Python programming, Machine Learning, and Deep Learning.
- Introduction to Image Inpainting: Introduces the theory behind diffusion models and how to train and apply them using Vertex AI.
- Encoder-Decoder Architectures: Explains the key components of encoder-decoder architectures and how to train and use these models.
- Attention Mechanisms: Teaches how attention mechanisms work and how they can improve the performance of machine learning tasks such as translation, summarization, and question answering.
- Transformer Models and BERT: Explains the key components of transformer architectures and how to use them to build BERT models.
- Creating Image Captioning Models: Teaches how to create image captioning models using deep learning.
How can you join these courses?
This learning path is hosted on the Google Cloud platform. Click here to enroll in one of the courses in the Generative AI Learning Path.
Remember, these are not the only free courses available on the Google Cloud platform. There are also other interesting courses such as the Data Engineer Learning Path, Data Analyst Learning Path, and more. Click here to explore the complete catalog on Google Cloud Skill Boost.