Gen AI: Unlock Foundational Concepts
Earned maj 31, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned maj 31, 2025 EDT
Introduction to Vertex AI Studio
Earned maj 31, 2025 EDT
Working with Notebooks in Vertex AI
Earned maj 31, 2025 EDT
Vector Search and Embeddings
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: interpretowalność i przejrzystość
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: prywatność i bezpieczeństwo
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia
Earned maj 31, 2025 EDT
Transformer Models and BERT Model
Earned maj 31, 2025 EDT
Encoder-Decoder Architecture
Earned maj 27, 2025 EDT
Attention Mechanism
Earned maj 27, 2025 EDT
Gemini for Application Developers
Earned maj 25, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned maj 25, 2025 EDT
Gemini for Data Scientists and Analysts
Earned maj 25, 2025 EDT
Gen AI: Beyond the Chatbot
Earned maj 23, 2025 EDT
Customer Engagement Suite with Google AI Architecture
Earned gru 10, 2024 EST
Conversational AI Voice and Chat Integrations
Earned gru 6, 2024 EST
Prompt Design in Vertex AI
Earned gru 5, 2024 EST
Advanced Conversation Design
Earned lis 30, 2024 EST
Conversation Design Fundamentals
Earned lis 30, 2024 EST
Advanced Performance Measurement
Earned lis 29, 2024 EST
Basic Performance Measurement
Earned lis 28, 2024 EST
Advanced Webhook Concepts
Earned lis 27, 2024 EST
Webhook fundamentals
Earned lis 27, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned lis 20, 2024 EST
Gemini for Cloud Architects
Earned lis 19, 2024 EST
Gemini for end-to-end SDLC
Earned lis 19, 2024 EST
Gemini for Security Engineers
Earned lis 19, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud - Polski
Earned lis 18, 2024 EST
Introduction to Data Analytics on Google Cloud
Earned lis 18, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned lis 17, 2024 EST
Introduction to Responsible AI - Polski
Earned lis 14, 2024 EST
Machine Learning Operations (MLOps) for Generative AI
Earned lis 14, 2024 EST
Introduction to Image Generation
Earned lis 14, 2024 EST
Introduction to Large Language Models - Polski
Earned lis 14, 2024 EST
Introduction to Generative AI - Polski
Earned lis 13, 2024 EST
Professional Machine Learning Engineer Study Guide
Earned lis 13, 2024 EST
Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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Earn a skill badge by completing the Using the Google Cloud Speech API quest, where you learn how create a Speech-to-Text API request, transcribe audio speech to text, and transcribe speech. 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, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Enhance the navigation experience of your website by using generative AI to provide a better search experience for your users. In this course, you learn how to use Vertex AI Search to provide your website users a generative search experience enabling them to discover content offered by the website. As a website editor, you also learn how to use generative AI to quickly and efficiently translate and improve the content using suggestions.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
Duet AI was renamed to Gemini, our next-generation model.
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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.
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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google's gen AI applications, such as Gemini for Workspace and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.
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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud?
In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.
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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
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Na tym szkoleniu przedstawiamy koncepcje interpretowalności i przejrzystości AI. Omawiamy na nim, jak ważna jest przejrzystość AI dla deweloperów i inżynierów. Pokazujemy praktyczne techniki i narzędzia, które pomagają osiągnąć interpretowalność oraz przejrzystość zarówno w danych, jak i modelach AI.
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To szkolenie wprowadza w ważne kwestie dotyczące prywatności i bezpieczeństwa w dziedzinie AI. W jego trakcie przedstawiamy praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie prywatności i bezpieczeństwa AI przy użyciu usług Google Cloud oraz narzędzi open source.
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Na tym szkoleniu przedstawiamy koncepcje odpowiedzialnej AI i zasad dotyczących AI. Omawiamy praktyczne metody identyfikowania obiektywności i uprzedzeń, a także ograniczania występowania uprzedzeń podczas używania AI/ML. W trakcie szkolenia przedstawiamy też praktyczne techniki i narzędzia, które umożliwiają wdrożenie sprawdzonych metod w zakresie odpowiedzialnej AI przy użyciu usług Google Cloud oraz narzędzi open source.
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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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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In this course, you will learn the advanced conversational design principles for both the Voice and Caht channels to craft engaging and effective end-to-end experiences that emulate human-like interactions.
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This course explores the foundational principles of conversation design to craft engaging and effective chatbot experiences that emulate human-like experiences.
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In this course, you will learn about advanced methods and tools to monitor the performance of your virtual agents in Dialogflow CX
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This course explores the fundamentals of the feedback loop process for Virtual Agent development and introduces the native capabilities within Dialogflow CX that support it
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This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Virtual Agent self-service experiences.
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In this course, you will learn the important role that different types of webhooks play in Dialogflow CX development, and how to effectively integrate them into your routine configuration of a Virtual Agent.
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This course helps learners create a study plan for the PDE (Professional Data 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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC).
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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Im szerzej wykorzystuje się w firmach sztuczną inteligencję i systemy uczące się, tym większej wagi nabiera odpowiedzialne podejście do opracowywania tych technologii. Wielu organizacjom trudniej jest jednak wprowadzić zasady odpowiedzialnej AI w praktyce niż tylko o tym rozmawiać. To szkolenie jest przeznaczone dla osób, które chcą się dowiedzieć, jak wdrożyć odpowiedzialną AI w swojej organizacji.
W jego trakcie dowiesz się, jak robimy to w Google Cloud, oraz poznasz sprawdzone metody i wnioski z naszych działań w tym zakresie. Pomoże Ci to opracować własne podejście do odpowiedzialnej AI.
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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.
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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest odpowiedzialna AI i dlaczego jest ważna, oraz przedstawienie, jak Google wprowadza ją w swoich usługach. Szkolenie zawiera także wprowadzenie do siedmiu zasad Google dotyczących sztucznej inteligencji.
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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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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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To szybkie szkolenie dla początkujących wyjaśnia, czym są duże modele językowe (LLM) oraz jakie są ich zastosowania. Przedstawia również możliwości zwiększenia ich wydajności przez dostrajanie przy użyciu promptów oraz narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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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.
Analyze Speech and Language with Google APIs
Earned sie 30, 2025 EDT
Using the Google Cloud Speech API
Earned sie 29, 2025 EDT
Website Modernization with Generative AI on Google Cloud
Earned sie 3, 2025 EDT
Gemini for DevOps Engineers
Earned sie 3, 2025 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned sie 3, 2025 EDT
Gemini for Network Engineers
Earned sie 3, 2025 EDT
Introduction to Security in the World of AI
Earned sie 1, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned cze 7, 2025 EDT
Gen AI Apps: Transform Your Work
Earned cze 1, 2025 EDT
Gen AI: Navigate the Landscape
Earned cze 1, 2025 EDT
Create Image Captioning Models
Earned cze 1, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned maj 31, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned maj 31, 2025 EDT
Introduction to Vertex AI Studio
Earned maj 31, 2025 EDT
Working with Notebooks in Vertex AI
Earned maj 31, 2025 EDT
Vector Search and Embeddings
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: interpretowalność i przejrzystość
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: prywatność i bezpieczeństwo
Earned maj 31, 2025 EDT
Odpowiedzialna AI dla deweloperów: obiektywność i uprzedzenia
Earned maj 31, 2025 EDT
Transformer Models and BERT Model
Earned maj 31, 2025 EDT
Encoder-Decoder Architecture
Earned maj 27, 2025 EDT
Attention Mechanism
Earned maj 27, 2025 EDT
Gemini for Application Developers
Earned maj 25, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned maj 25, 2025 EDT
Gemini for Data Scientists and Analysts
Earned maj 25, 2025 EDT
Gen AI: Beyond the Chatbot
Earned maj 23, 2025 EDT
Customer Engagement Suite with Google AI Architecture
Earned gru 10, 2024 EST
Conversational AI Voice and Chat Integrations
Earned gru 6, 2024 EST
Prompt Design in Vertex AI
Earned gru 5, 2024 EST
Advanced Conversation Design
Earned lis 30, 2024 EST
Conversation Design Fundamentals
Earned lis 30, 2024 EST
Advanced Performance Measurement
Earned lis 29, 2024 EST
Basic Performance Measurement
Earned lis 28, 2024 EST
Advanced Webhook Concepts
Earned lis 27, 2024 EST
Webhook fundamentals
Earned lis 27, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned lis 20, 2024 EST
Gemini for Cloud Architects
Earned lis 19, 2024 EST
Gemini for end-to-end SDLC
Earned lis 19, 2024 EST
Gemini for Security Engineers
Earned lis 19, 2024 EST
Responsible AI: Applying AI Principles with Google Cloud - Polski
Earned lis 18, 2024 EST
Introduction to Data Analytics on Google Cloud
Earned lis 18, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned lis 17, 2024 EST
Introduction to Responsible AI - Polski
Earned lis 14, 2024 EST
Machine Learning Operations (MLOps) for Generative AI
Earned lis 14, 2024 EST
Introduction to Image Generation
Earned lis 14, 2024 EST
Introduction to Large Language Models - Polski
Earned lis 14, 2024 EST
Introduction to Generative AI - Polski
Earned lis 13, 2024 EST
Professional Machine Learning Engineer Study Guide
Earned lis 13, 2024 EST