Prompt Design in Vertex AI
Earned nov. 7, 2024 EST
Flutter Essentials
Earned nov. 4, 2024 EST
Professional Machine Learning Engineer Study Guide
Earned oct. 21, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned oct. 18, 2024 EDT
Developing a Google SRE Culture
Earned oct. 17, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned oct. 10, 2024 EDT
Introduction to Data Analytics in Google Cloud
Earned oct. 10, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned oct. 9, 2024 EDT
Introduction to Responsible AI
Earned oct. 8, 2024 EDT
Introduction to Large Language Models
Earned oct. 8, 2024 EDT
Introduction to Generative AI
Earned oct. 8, 2024 EDT
Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Flutter is Google's UI toolkit for building beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. In this quest you will learn how to create a Flutter app using generated template code. Be sure to tag #flutterfestival in your social posts!
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This course helps learners create a study plan for the PMLE (Professional Machine Learning Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 7 AI principles.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
Prompt Design in Vertex AI
Earned nov. 7, 2024 EST
Flutter Essentials
Earned nov. 4, 2024 EST
Professional Machine Learning Engineer Study Guide
Earned oct. 21, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned oct. 18, 2024 EDT
Developing a Google SRE Culture
Earned oct. 17, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned oct. 10, 2024 EDT
Introduction to Data Analytics in Google Cloud
Earned oct. 10, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned oct. 9, 2024 EDT
Introduction to Responsible AI
Earned oct. 8, 2024 EDT
Introduction to Large Language Models
Earned oct. 8, 2024 EDT
Introduction to Generative AI
Earned oct. 8, 2024 EDT