Unlock the Potential of Generative AI with this Free Learning Path by Google

Unlock the Potential of Generative AI with this Free Learning Path by Google

Introduction:

If you’re interested in exploring the potential of Generative AI Models and their applications, you’re in luck. Google Cloud has released the Generative AI Learning Path, a collection of free courses that cover everything from the basics of Generative AI to advanced tools like Generative AI Studio for building customized AI models. This article provides an overview of seven courses within the learning path, allowing you to understand the concepts behind Large Language Models and create new AI solutions. Whether you’re new to AI or already have a background in machine learning, these courses offer valuable insights and practical knowledge. So, let’s dive in and start discovering the world of Generative AI!

Full Article: Unlock the Potential of Generative AI with this Free Learning Path by Google

Google Cloud has released a Generative AI Learning Path, offering a collection of free courses for those interested in exploring the potential of Generative AI Models. These courses range from basic concepts to more advanced tools like Generative AI Studio, which allows users to build customized generative AI models. In this article, we will highlight seven of these courses, providing an overview of the knowledge and skills they offer.

Introduction to Generative AI: This course, taught by Dr. Gwendolyn Stripling, introduces the fundamental concepts of Generative AI and its applications. It covers the differences between Generative AI, AI, Machine Learning, and Deep Learning. The course also explains key concepts such as transformers, hallucinations, and Large Language Models.

Introduction to Large Language Models: This course provides a high-level introduction to Language Models and their applications, such as text classification, question answering, and document summarization. It also showcases Google’s Generative AI Development tools, which enable users to build applications without code.

Introduction to Image Generation: This course focuses on diffusion models, which are models that generate images. It covers various approaches, including Variational Autoencoders, Generative Adversarial Models, and Autoregressive Models. The course provides examples of unconditioned and conditioned image generation, such as human face synthesis, image inpainting, and text-guided image-to-image generation.

Attention Mechanism: In this short course, learners will explore the attention mechanism, a key concept behind transformers and Large Language Models. The course explains how the attention mechanism works in tasks like machine translation, text summarization, and question answering.

Transformer Models and BERT Model: This course delves into transformer architecture, the underlying concept behind the BERT model. It offers an overview of BERT and its application in tasks like single-sentence classification and question answering. This course includes a laboratory component that requires prior knowledge of Python and TensorFlow.

Create Image Captioning Models: This course focuses on Image Captioning Models, which generate text captions based on input images. It explores the encoder-decoder structure, attention mechanism, and transformer used to predict captions for images. Like the previous course, this one also includes a laboratory component for hands-on practice.

Introduction to Generative AI Studio: The final course introduces Generative AI Studio, which allows users to easily build generative models without code or with low code. The course explains the core concepts of Generative AI and showcases use cases such as code generation, information extraction, and virtual assistance. Generative AI Studio is part of the Vertex AI platform, which enables users to manage the machine learning cycle, from building to deployment.

These courses offer a comprehensive overview of Generative AI, catering to both beginners and those with a machine learning background. By completing these courses, learners can gain valuable insights into the concepts and applications of Generative AI. If you know of any other free courses on Generative AI, please share your suggestions in the comments.

Summary: Unlock the Potential of Generative AI with this Free Learning Path by Google

Google Cloud has released the Generative AI Learning Path, a collection of free courses that provide an in-depth understanding of Generative AI Models and their applications. This article highlights seven of these courses, covering topics such as Introduction to Generative AI, Large Language Models, Image Generation, Attention Mechanism, Transformer Models, Create Image Captioning Models, and Introduction to Generative AI Studio. Each course includes videos and suggested readings, making it easy for learners to grasp the concepts and tools involved in generative AI. Whether you are new to AI or have a background in machine learning, these courses offer valuable insights into generative AI.

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