Course: Generative AI on Google Cloud Platform (GCP)
duration: 12 hours |
Language: English (US) |
access duration: 180 days |

Details
The world of artificial intelligence is rapidly evolving, and generative AI is leading the charge. This course equips you with the knowledge to leverage the power of Google Cloud Platform (GCP) for your generative AI projects.
You'll gain a deep understanding of generative AI concepts, its advantages and limitations, and its role within the broader field of machine learning. You also explore Vertex AI, the heart of GCP's machine learning offerings, and discover how it streamlines generative AI workflows and empowers you to build better models. At last you wil
delve into Generative AI Studio, a powerful cloud-based tool for rapid prototyping and deployment of your generative AI models. Learn to fine-tune language models, evaluate performance, and ultimately deploy them for real-world use.
Result
By the end of this course, you'll have the knowledge to:
- Confidently leverage Vertex AI for generative AI projects.
- Design effective prompts and train generative AI models.
- Evaluate model performance and deploy your creations.
- Develop innovative applications powered by GCP's generative AI tools.
Prerequisites
No formal prerequisites. Some experience in working with GCP is recommended.
Content
Generative AI on Google Cloud Platform (GCP)
Generative AI on GCP: An Introduction
Generative artificial intelligence (AI) has taken the world by storm. Chatbots, photo creation, document writing, and other practical applications are everywhere, and they're gaining in popularity and sophistication. Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence. In this course, you'll be introduced to generative AI, beginning with GCP and its generative AI offerings. You will discover the advantages and disadvantages of generative AI and features of GCP machine learning (ML). Then you'll learn about the generative AI life cycle, image generation, natural language processing (NLP), and best practices for developing generative AI. Finally, you'll explore GCP privacy, security, and compliance considerations, monitoring and logging with GCP, and some real-world generative AI use cases.
Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI
Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence (AI). A main component of that toolbox is Google's Vertex AI platform, which can aid organizations in streamlining machine learning (ML) workflows and deliver better machine learning models. In this course, you'll be introduced to Vertex AI, beginning with an overview of its features, model deployment, and end-to-end workflow. Then you'll explore pros and cons of Vertex AI, how it can be used to accelerate development, and model selection, training, and evaluation considerations. Finally, you'll learn about Vertex AI integration, data preparation, feature engineering, model evaluation, and Vertex AI success stories.
Generative AI on GCP: Harnessing Generative AI with Vertex AI
A main component of the Google Cloud Platform (GCP) machine learning offering is Google's Vertex AI Platform, which provides tools that can aid organizations in leveraging Vertex AI for generative artificial intelligence (GenAI) projects. This course investigates the unique support and capabilities offered by Vertex AI specifically for generative AI models, empowering learners to unlock their creative potential. In this course, you will dig into harnessing generative AI using Vertex AI, beginning with an overview of generative AI support in Vertex AI, Vertex AI's generative AI models, and the features and uses of Google's Generative AI Studio. Then you will discover the Vertex AI API, explore Vertex AI Model Garden, and create custom models in Vertex AI. Finally, you will learn about responsible AI with safety filters and find out how to use Vertex AI Search and Conversation. After completing this course, you will be able to confidently leverage Vertex AI to build generative AI models.
Generative AI on GCP: Deep Dive Into Generative AI Studio
Generative artificial intelligence (AI) has taken the world by storm, and Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence. Google's Generative AI Studio is a cloud console tool for rapid prototyping and testing of generative AI models and leverages the power of Vertex AI, allowing developers to interact, tune, and deploy large-scale AI models. In this course, you will take a deep dive into Generative AI Studio, beginning with generative AI prompt design, model training, and tuning language models. Then you will explore model performance evaluation and generative AI deployment. Next, you will focus on case studies and practical examples to discover how organizations use GCP generative AI. Finally, you will learn how to convert speech to text and prototype language applications.
Generative AI on GCP: Building Generative AI-powered Apps in GCP
Google Cloud Platform (GCP) has a wide range of powerful generative artificial intelligence (AI) services that can leverage the power of modern AI. Using these services, developers can build powerful applications with GCP, and with the proper use of various technologies, developers new to GCP can gain the knowledge and skills necessary to develop and deploy cutting-edge generative AI applications. In this course, you will create a generative AI-powered app in GCP, beginning with planning and building a generative AI model, GCP environment setup, and Python environment creation. Then you will learn how to build and train a generator and a discriminator with TensorFlow. Next, you will build and run a training loop, and dockerize the training script. Finally, you will deploy your finished model to an application programming interface (API) endpoint and test that model.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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