Estimated reading time: 4 minutes
1. Introduction to Generative AI
This microlearning course offers an introductory-level exploration of Generative AI, delving into its principles, applications, and distinctions from conventional machine-learning approaches. Additionally, it provides insights into Google Tools that facilitate the creation of your own Generative AI applications. Anticipate dedicating around 45 minutes to successfully conclude this course.
2. Introduction to Large Language Models
Embark on a foundational microlearning journey with our introductory course, delving into the realm of large language models (LLM). Discover their applications across various domains and harness the power of prompt tuning to elevate LLM capabilities. Unveil the array of Google tools at your disposal for crafting your own Generation AI applications. Expect a rewarding experience that can be completed in around 45 minutes.
3. Introduction to Responsible AI
This microlearning course offers an introduction to responsible AI at a beginner level, elucidating its significance and Google’s approach to its implementation in products. Additionally, it provides insights into Google’s 7 AI principles.
4. Generative AI Fundamentals
Earn a skill badge by successfully completing the Introduction to Generative AI, Introduction to Large Language Models, and Introduction to Responsible AI courses. By successfully completing the final quiz, you’ll showcase your grasp of fundamental concepts in generative AI.
A skill badge is a digital credential granted by Google Cloud to acknowledge your expertise in Google Cloud products and services. Display your skill badge by setting your profile to public and adding it to your social media bio.
5. Introduction to Image Generation
This course presents diffusion models, a group of machine-learning models that have demonstrated significant potential in the realm of image generation. These models draw inspiration from the field of physics, particularly thermodynamics, and have gained substantial traction in both academic research and practical applications over recent years. Diffusion models serve as the foundation for numerous cutting-edge image generation techniques and resources available on Google Cloud. Through this course, you will delve into the fundamentals of diffusion models, and their theoretical framework, and gain insights into training and deploying them using Vertex AI.
6. Encoder-Decoder Architecture
This course provides an overview of the encoder-decoder architecture, a robust and widely used machine learning framework designed for sequence-to-sequence tasks like machine translation, text summarization, and question answering. You’ll delve into the essential elements of the encoder-decoder structure and grasp the training and deployment aspects of these models. In the accompanying practical demonstration, you’ll engage with TensorFlow to create a basic encoder-decoder implementation for generating poetry right from scratch.
7. Attention Mechanism
In this course, you’ll be introduced to the attention mechanism, a potent tool enabling neural networks to concentrate on specific segments of an input sequence. You’ll grasp the functioning of attention and its potential to enhance the efficacy of diverse machine learning assignments, spanning from machine translation and text summarization to question answering. The estimated duration for completing this course is approximately 45 minutes.
8. Transformer Models and BERT Model
In this course, you’ll be introduced to the Transformer architecture and delve into the Bidirectional Encoder Representations from the Transformers (BERT) model. You’ll gain insights into the core elements of the Transformer architecture, including the self-attention mechanism, and discover how it forms the foundation of the BERT model. Furthermore, you’ll explore the diverse range of applications for BERT, encompassing text classification, question answering, and natural language inference. Completion of this course is expected to take around 45 minutes.
9. Create Image Captioning Models
In this course, you will gain the skills to craft an image captioning model through deep learning techniques. You’ll delve into the various elements that constitute an image captioning model, including both the encoder and decoder components, mastering the art of training and assessing your model effectively. Upon completing this course, you’ll possess the capability to fashion your own image captioning models and apply them seamlessly to produce captivating descriptions for images.
10. Introduction to Generative AI Studio
This course provides an introduction to Generative AI Studio, a product within Vertex AI designed to enable the creation and customization of generative AI models for seamless integration into your applications. Throughout this course, you will gain insights into the functionality, features, and choices offered by Generative AI Studio. Through hands-on demonstrations, you’ll learn the practical application of this tool. The course culminates in a hands-on lab that allows you to put your newfound knowledge into practice, followed by a quiz to assess your understanding.
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