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This Udemy course is your ticket to the world of Artificial Intelligence (AI). Anyone can join - you don't need any special knowledge, just an internet connection. Dream of becoming an AI expert? Or just want to understand how AI works and how to use it in your daily life or work? Then this course is for you. We start from the basics and slowly build up, so you learn how to use AI techniques in all sorts of situations. You also get the chance to learn how to design and optimize AI prompts, so you can get started as an AI prompt engineer. You'll find that AI is not just for techies. AI offers so many opportunities and chances, also for you! And the beauty is, you learn using real AI models. We use well-known AI text models like ChatGPT and AI image models like Midjourney. This way, you'll discover how to deploy these handy tools for all sorts of things, from simple daily tasks to more complex workflows. In short, this course is for anyone who wants to discover the power and potential of AI and learn how to deploy AI to make their life easier, more efficient, and more enjoyable. Whether you're a student, entrepreneur or techie, this course has something to offer for everyone. Hop on board and explore the world of AI with us!

The greater the use of enterprise artificial intelligence and machine learning, the more important it is to develop them responsibly. For many, talking about responsible AI may be easier, but putting it into practice is a challenge. If you are interested in learning how to operationalize responsible AI in your organization, this course is for you. In it, you'll learn how Google Cloud does this today, as well as review best practices and lessons learned to create a foundation for crafting your own approach to responsible AI.

The more artificial intelligence and machine learning systems are used in companies, the more important a responsible approach to developing these technologies becomes. However, many organizations find it more difficult to implement the principles of responsible AI in practice rather than just talk about it. This training is intended for people who want to learn how to implement responsible AI in their organization. During it, you will learn how we do it in Google Cloud, and learn proven methods and conclusions from our activities in this area. This will help you develop your own approach to responsible AI.

"As enterprises adopt more artificial intelligence and machine learning, it becomes more important to build these technologies in a responsible way. But for many companies, truly practicing Responsible AI is not easy. If you are interested in learning how to practice Responsible AI in your organization, this course is for you. This course will introduce how Google Cloud is currently implementing Responsible AI, and summarize the best practices and lessons learned so that you can use this as a framework to build your own Responsible AI approach.

This course introduces artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud for building predictive and generative AI projects. It explores the technologies, products, and tools available across the data-to-AI lifecycle, including AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers advance their skills and knowledge through engaging learning activities and hands-on exercises.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use the What-if Tool to identify potential biases in a model trained on mortgage loan applications.

“Learn about the evolution of artificial intelligence investing and online wealth management. Online investing and wealth management have become easier than ever, but will artificial intelligence investing really work? What are the problems? In this course, you'll learn how technology has changed the way we invest. Let’s learn about the principles of artificial intelligence-based online asset management platforms and robo-advisors, and consider why they are successful. Moving from a human-based data-driven investment strategy to a neural network strategy, the investment decision ability of artificial intelligence and the role of artificial intelligence and machine learning. “You are welcome.”

By incorporating machine learning into data pipelines, companies can extract more insights. In this course, we show several ways to add machine learning to data pipelines on Google Cloud Platform, depending on the level of customization required. We explain how to use AutoML when you need little or no customization. For more personalized machine learning capabilities, we show you how to use AI Platform Notebooks and BigQuery Machine Learning. We also explain how to produce machine learning solutions using Kubeflow. Additionally, there will be hands-on activities creating ML models on Google Cloud Platform using QwikLabs.

Machine learning and AI projects require managing diverse data sources, vast data volumes, model and parameter development, and conducting numerous test and evaluation experiments. Overseeing and tracking these aspects of a program can quickly become an overwhelming task. This course will introduce you to Machine Learning Operations tools that manage this workload. You will learn to use the Weights & Biases platform which makes it easy to track your experiments, run and version your data, and collaborate with your team.

Artificial intelligence (AI) and machine learning (ML) represent important developments in information technology that are transforming a wide variety of industries. The ""Innovating with Google Cloud Artificial Intelligence"" course shows how organizations can use AI and ML to transform business processes. As part of the Cloud Digital Leader learning program, the aim of this course is to help you grow professionally and develop the future of your own business.

This is a focused introductory course that aims to explain what AI ethics are, why they are important, and how Google practices AI ethics in its products. It also presents the 7 principles of Google's AI.

Stable diffusion is the world's most popular artificial intelligence image generation tool . Unlike competitors like midjourney or dall-e 2, stable diffusion is free and open source . In addition you can use it locally directly on your computer. To run stable diffusion locally, you must have an nvidia graphics card with at least 4gb of vram. This comprehensive training will allow you to fully master AI image generation with stable diffusion . You will learn all the techniques and tricks to make the best use of stable diffusion. With stable diffusion, you have the ability to create any type of image, limited only by your imagination. Use it to create photos, drawings, and illustrations for your products, blog, or even video games. You can also use it to make posters, goodies, books, and videos, and even use the resulting images for commercial projects. MOST IMPORTANT - Providing with Literally 1 Million prompts to combine with (No one has Access) - Providing step wise guide to Make Money Using Stable Diffusion This comprehensive course will teach you how to: - Install stable diffusion on your local machine - Generate images from text - Optimize the generated images for a professional result - Write text that will be effectively interpreted by stable diffusion's ai - Enlarge and enhance generated images - Create an image based on another image - Utilise various online tools to assist with image generation - Make Commissions Using Stable Diffusions. Stable diffusion is a highly versatile tool with unlimited potential for generating and using images. By completing this creative training, you will become a pro at using stable diffusion and may even find it addictive. The possibilities are endless.