12 053 cours
Dans ce projet guidé d'une heure. vous apprendrez comment créer un compte professionnel sur Pinterest, faire de la publicité et savoir comment réussir sur Pinterest. À la fin de ce projet, vous aurez appris à faire de la publicité sur Pinterest.
Langue d’origine
By the end of this project you will create an affinity diagram using Creately.com. Learning to collect and organize ideas and information increases productivity and fosters positive teamwork. Learners will engage in the Affinity process to develop an understanding of how to spark, gather, consolidate, sort and present ideas and information.
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En este quinto curso del Certificado de Ciberseguridad de Google, explorarás los conceptos de activos, amenazas y vulnerabilidades. Primero conocerás cómo se clasifican los activos. Luego, te profundizarás sobre las amenazas y vulnerabilidades más comunes, así como los controles de seguridad que utilizan las organizaciones para proteger la información valiosa y mitigar el riesgo. Además, practicarás el proceso de modelado de amenazas y desarrollarás una mentalidad de atacante. También, aprenderás tácticas para anticiparte a los riesgos de seguridad. Te guiarán especialistas de Google, que actualmente trabajan en ciberseguridad, con actividades prácticas y ejemplos que simulan tareas comunes y frecuentes de este campo. Todo esto te ayudará a desarrollar tus habilidades y prepararte para trabajar. Los/las estudiantes que completen este certificado estarán preparados/as para solicitar trabajo en el área de la ciberseguridad, en un nivel inicial. No se necesita experiencia previa.
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By the end of this course, learners will be able to apply detailed UV-mapped textures, create lifelike facial and body details, refine clothing surfaces, and design realistic shaders for eyes and materials in 3ds Max. This course takes students step-by-step through the professional workflow of texturing characters in 3ds Max using Photoshop and UV unwrapping. Starting with the head, lips, and eyebrows, learners gain hands-on experience in painting and aligning textures for natural skin tones and expressive facial features. The journey continues with body, hands, and clothing, where learners explore how to craft fabric details, refine jacket seams, and add subtle realism through burn and shading techniques. Finally, learners will master the use of shaders, enhancing eyeballs with glossiness and reflection to achieve cinematic realism. What makes this course unique is its practical, project-based approach—focused on Shrek-style character modeling—that bridges technical precision with creative artistry. Upon completion, learners will possess industry-ready skills to texture, shade, and polish 3D characters, making them production-ready for animation, games, or film projects.
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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.
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This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will get hands-on practice configuring and deploying an App Engine instance with the APIs Explorer tool.
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In real-world machine learning work, building a model is only half the job. Knowing how to evaluate it, explain its weaknesses, and defend improvements is what makes your work trustworthy. In this course, you will learn how to evaluate regression and classification models using the right metrics, diagnose where models systematically fail, and determine whether performance differences actually matter. You will practice selecting RMSE and MAE for reporting housing-price models, analyzing confusion matrices to uncover false-positive patterns in spam filters, and using bootstrapping to test whether AUC improvements are statistically significant. Through short videos, guided coaching conversations, hands-on activities, and an ungraded lab, you will build confidence in interpreting model performance the way it is done on real teams. By the end of the course, you will be able to justify your evaluation choices and make evidence-based model decisions.
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By the end of this project, you will have developed LibreOffice Base queries that provide data for use in sales analysis. An organization that sells products or services finds it useful to know which products are selling, whether they are priced appropriately, and which customers are purchasing them. Providing that kind of data gives the organization better targets for fine tuning its product mix and customer base. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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This is the fifth course in the Google Cybersecurity Certificate. These courses will further explore the importance of protecting organizational assets from threats, risks, and vulnerabilities. They will also continue to develop an understanding of asset classification and how to use the National Institute of Standards and Technology’s (NIST) Cybersecurity Framework (CSF), as well as security controls, to protect assets and mitigate risk. Additionally, learners will gain an understanding of how to develop a threat actor mindset to help protect assets from ever-evolving threat actor tactics and techniques. By the end of this course, you will: - Learn effective data handling processes. - Discuss the role of encryption and hashing in securing assets. - Describe how to effectively use authentication and authorization. - Explain how common vulnerability exposures are identified by MITRE. - Analyze an attack surface to find risks and vulnerabilities. - Identify threats, such as social engineering, malware, and web-based exploits. - Summarize the threat modeling process.
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This Teach Out does not issue certificates of completion. Algorithms – and algorithmic bias – are making regular appearances in the news, and increasingly, are being recognized as a policy issue. But what is an algorithm, exactly? And what does it mean when someone describes an algorithm as biased? This Teach-Out will encourage policy makers, agency leaders, and others in similar positions to identify algorithms that are already in use and make connections to broader ideas about fairness, justice, and equity. After completing the Teach-Out, learners will be able to participate in discussions around algorithmic bias, inform others about how algorithms can perpetuate existing disparities, and take steps to reduce the impact of algorithmic bias on the people and communities they serve.
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推論のための BigQuery ML の概要、データ アナリストがこれを使用すべき理由、そのユースケース、サポートされる ML モデルについて学びます。また、これらの ML モデルを BigQuery で作成し、管理する方法も学びます。
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This course introduces you to Cloud Computing and Oracle's Cloud Solutions which include Oracle Cloud Infrastructure and Oracle Cloud Applications. Quick product tours help you experience the capabilities of our OCI and SaaS Platforms.
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