AS time went on, the use of Artificial Intelligence slowly became acceptable in the current generation thanks to its convenience and innovation.
And with its continuous contribution to society, Google just released 9 free online courses that you can take to master the use of AI.
The free course includes videos and a quiz that redirects users to know what, where, and how artificial intelligence is being used. After completing the course, the learner will be able to obtain their badge.
Introduction to Generative AI
The objective of this introductory is to give the basic level of microlearning course to define the use of generative artificial intelligence. Under this course, users will be able to describe its applications and highlight its distinctions from more conventional machine learning techniques.
This course will teach you the definition of Generative AI, how Generative AI works, and the description of Generative AI Model Types and AI Applications.
The course also covers Google tools to help you develop your own Gen AI apps. It also covers Google Tools to help you develop your own Gen AI apps.
To access this course, click this link:
Image Generation
The Image Generation course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. This will also teach you the theory behind diffusion models and how to train and deploy them on Vertex AI.
The said model draws inspiration from the subject of physics, specifically through thermodynamics, and within the last few years, the diffusion model became well-received in both research and industry.
Upon taking this course, the user will be able to learn how diffusion models work, the real use cases for diffusion models, unconditioned diffusion models, and advancements in diffusion models (text-to-image).
To access this course, click this link:
Responsible AI
The Responsible AI course is aimed to explain what responsible AI is about and why it is important.
Taking this course will help you understand why Google has put AI principles in place and how you’ll identify the need for responsible AI practice within an organization.
Aside from learning its principles, you’ll also be able to recognize that decisions made at all stages of a project have an impact on responsible AI and that the organization can design AI to fit its business needs and values.
The course will also make you understand how Google implements responsible AI in its products along with Google’s 7 AI principles.
To access this course, click this link:
Large Language Models
This course is an introduction to what the Large Language Model (LLM) is all about. It will explore how they can be utilized and how you can use prompt tuning to enhance LLM performance.
To access this course, click this link:
Encoder-Decoder Architecture
The Encoder-Decoder Architecture course offers a detailed explanation–and understanding of its operation and role in various AI applications.
Through this course, you will learn about the main components of the encoder-decoder architecture and how to train and serve these models. In addition to this, you’ll also be able to write your encoder-decoder model in Keras.
To access this course, click this link:
Transformer and BERT models
The Transformer Architecture and the Bidirectional Encoder Representation from Transformers (BERT) model is a course where you can learn about the main components of the Transformer architecture includes self-attention mechanism and how it is used to build the BERT model.
Adding to that, you can also learn about the different tasks that BERT can be used for including text classification, question answering, and natural language inference.
To access this course, click this link:
Attention Mechanism
The attention mechanism course will introduce you to the attention mechanism.
It is a powerful technique that will allow neural networks to focus on specific parts of an input sequence. Through this course, you’ll be able to learn how attention works and how it can be used to improve performance in machine translation, text summarization, and question-answering.
To access this course, click this link:
Generative AI studio
The Generative AI studio (also known as Vertex AI studio) is a tool that is used to prototype and customize generative AI models.
Through this course, you’ll be able to explore the generative AI workflow through immersive lessons, engaging demos, and a hands-on lab.
You’ll also be able to learn how to leverage Vertex AI studio for Gemini multimodal applications, prompt design, and model tuning.
To access this course, click this link:
Image Recognition
Through this course, you will be able to learn how to create an image captioning model by using deep learning through different components of an image captioning model such as the encoder and decoder, and how to train and evaluate your model.
The image recognition course will also teach you how you’ll be able to create your image captioning models and use them to generate captions for images.
To access this course, click this link:
