12 053 cours
Kursus ini, yang dirancang khusus untuk tenaga kesehatan, menjelaskan AI generatif yang menjadi terobosan terbaru dalam kecerdasan buatan, dan model bahasa besar (LLM) yang mendukungnya. Temukan penerapan AI generatif di dunia nyata dalam pengaturan layanan kesehatan dan kuasai seni membuat perintah efektif yang disesuaikan dengan sasaran Anda.
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This course equips learners with the essential skills to analyze, configure, and apply Unix file permission models and shell environment settings with confidence. Starting from foundational concepts like symbolic and numeric permission representations, learners will explore user and group ownership management, special permission bits such as SUID, SGID, and Sticky Bit, and their impact on system security and accessibility. The course then transitions into Unix environment configuration, where learners will learn to define, export, and manage environment variables and startup profiles across both user and system levels. By the end of this course, learners will be able to interpret complex permission strings, modify access controls appropriately, and optimize the Unix environment for streamlined command execution and secure multi-user interactions. The course is ideal for aspiring system administrators, developers, and IT professionals seeking practical Unix competency for real-world applications.
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In this project-based course, you will follow your own interests to create a portfolio worthy single-frame viz or multi-frame data story that will be shared on Tableau Public. You will use all the skills taught in this Specialization to complete this project step-by-step, with guidance from your instructors along the way. You will first create a project proposal to identify your goals for the project, including the question you wish to answer or explore with data. You will then find data that will provide the information you are seeking. You will then import that data into Tableau and prepare it for analysis. Next you will create a dashboard that will allow you to explore the data in depth and identify meaningful insights. You will then give structure to your data story by writing the story arc in narrative form. Finally, you will consult your design checklist to craft the final viz or data story in Tableau. This is your opportunity to show the world what you’re capable of - so think big, and have confidence in your skills!
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이 강좌는 엔트리 레벨 IT 지원 전문가의 역할을 준비하는 것을 목표로 하는 강좌 중 첫 번째 강좌입니다. 이 강좌에서 여러분은 정보 기술(IT) 세계에 입문하게 됩니다. 또한 컴퓨터 하드웨어, 인터넷, 컴퓨터 소프트웨어, 문제 해결 및 고객 서비스와 같은 정보 기술의 다양한 면에 대해 배웁니다. 이 강좌에서는 이 수료증 과정에서 다룰 내용을 개괄적으로 이해할 수 있도록 마련된 다양한 IT 주제를 다룹니다. 이 강좌가 끝나면 다음을 할 수 있습니다. ● 바이너리 시스템 작동 방식 이해하기 ● 처음부터 컴퓨터 조립하기 ● 운영체제를 선택하여 컴퓨터에 설치하기 ● 인터넷이 무엇인지, 어떻게 작동하는지, 그리고 현대 세계에 미치는 영향을 이해하기 ● 애플리케이션이 작성되는 방법과 컴퓨터의 후드 아래에서 작동하는 방법 학습하기 ● 정보 기술(IT) 설정에서 일반적인 문제 해결 방법론과 소프트 스킬 활용하기
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En este proyecto, los alumnos aprenderán a administrar y programar su contenido en Facebook Creator Studio. Facebook Creator Studio tiene todas las herramientas que necesitas juntas para que puedas publicar tu contenido, administrarlo, monetizarlo y medir tu contenido. Puede hacer todo eso para todas sus páginas de Facebook y cuentas de Instagram. Facebook Creator Studio es la herramienta perfecta para administrar tu presencia en las redes sociales completamente gratis y en una plataforma que te permite hacerlo todo. En este proyecto, tendrá la oportunidad de aprender cómo puede ser eficaz en sus habilidades de gestión de redes sociales y cómo aprovechar las herramientas que ya tiene a mano. Si está buscando mejorar con las redes sociales, este es el proyecto guiado para usted. Facebook Creator Studio es gratis y está disponible para ti si tienes una página de Facebook.
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Gen AI is not just another technology change. It fundamentally alters how work is performed, how roles evolve, and how organizations adapt. In this course, you will learn how to manage Gen AI-driven transformation in a way that reflects its speed, variability, and continuous nature. You’ll understand how Gen AI changes the structure of work itself, shifting roles from execution to supervision and orchestration. You’ll learn why traditional change management approaches break down in this context, and how to replace them with more adaptive, iterative models. The course also introduces a practical maturity model to assess where organizations stand, and a set of common failure modes that explain why many Gen AI initiatives stall or collapse. What makes this course unique is its focus on how change actually behaves in Gen AI environments. Not just frameworks, but dynamics. By the end, you will be able to diagnose transformation challenges, anticipate resistance, and guide organizations through Gen AI adoption with clarity and control.
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Poor financial decisions cost businesses billions because leaders lack tools to properly evaluate options. Professionals who master financial analysis become trusted advisors. This course provides the financial toolkit essential for business success. Learn to dissect financial statements like forensic accountants, spotting hidden problems and opportunities. Master Excel-based modeling to build dynamic forecasts adapting to changing assumptions. Develop expertise in valuation from DCF to multiples approaches. Through hands-on labs with real company data, practice building models that withstand scrutiny while remaining accessible to operational managers. By completion, you'll confidently lead financial workstreams and translate numbers into narratives that drive decisions.
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This course is designed for those in roles with decision making power, to help them understand major topics to consider for using and developing Artificial Intelligence (AI) responsibly, including popular Generative AI tools like ChatGPT and others. It covers real-world examples of situations where AI was used in variety of fields and situations in ways hat revealed ethical concerns. Strategies are suggested to avoid doing harm working with AI, including a framework for working responsibly with AI. Unique Features of this Course - Broadly applicable to audiences of any field - Efficient yet effective overview of major ethical concerns - Beginner friendly for those who want to get started using generative AI tools - Practical tips for how to work with and develop AI tools more consciously - Examples of real-world uses of AI which have raised ethical debate Key Words Artificial Intelligence (AI), Ethics, Generative AI, Large Language Models (LLMs), Data Science Intended Audience - Professionals looking for an introduction to AI Ethics - Decision makers who may have to help write AI policies or determine how AI will be used at an institute - Anyone curious about how we can use AI more responsibly Note: It is helpful to have some fundamental knowledge about what AI is and how it works. This course is not intended as legal advice, we advise that learners seek expert ethical and legal guidance when writing policies or launching new AI projects . Learning Objectives - Describe key ethical concerns for using AI tools - Explain why AI should be thought of as a better computer, not a human replacement - Discuss the potential benefits of being transparent about the use of AI tools - Recognize real-world examples of AI usage that has resulted in ethical debate - Explain the necessity for independent validation of AI models - Identify possible mitigation strategies for major ethical concerns with regard to the algorithms underlying AI tools - Describe practices that can help you to adhere to more responsible AI use and development - Identify concepts and strategies for promoting social justice in AI use and development - Discuss nuances involved with consent in the use of AI - Describe a possible process for reflecting on ethical AI use and development Accessibility We are committed to making our content accessible and available to all. We welcome any feedback you might have at https://forms.gle/3sTZpctxzYyhj74NA. Questions related to accessibility accommodations should be directed to https://studentserviceportal.force.com/s/. PDF versions of this course can be found at https://hutchdatascience.org/AI_for_Decision_Makers/introduction-to-avoiding-ai-harm.html.
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Develop the ability to analyze SWIFT messaging systems, interpret MT formats, and evaluate operational controls used in investment banking settlements. This course enables learners to understand how financial institutions communicate securely through standardized SWIFT messages and how different message categories support payments, trade finance, and cash management. By completing this course, learners will gain practical insights into real-world banking operations, including customer payments (MT 103), trade finance instruments (MT 700), and interbank communication flows. They will also learn how to apply governance practices such as segregation of duties and internal controls to ensure secure and compliant financial messaging. What makes this course unique is its strong focus on applied learning through real SWIFT message structures and operational scenarios used in investment banking environments. Rather than just theory, it equips learners with job-relevant skills in financial messaging, transaction processing, and risk management—making it ideal for aspiring professionals in banking, finance, and payments operations.
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At the end of this project, you will have all the basic skills to create a professional business presentation with Piktochart, an online tool for creating and editing infographics and Marketing visuals of all kinds. You will be able to discover in detail the different features of the platform, and will be able to use its tools to create a professional, understandable and fun presentation.
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Welcome to the specialization course of NoSQL Systems. This course will be completed on six weeks, it will be supported with videos and exercises that will allow you to identify the differences between the relational and NoSQL databases. As part of these alternative technologies the student will learn the main characteristics and how to implement the typical NoSQL databases, such as Key-value, columnar, document and graph. Let's start! After completing this course, a learner will be able to ● Identify what type of NoSQL database to implement based on business requirements (key-value, document, full text, graph, etc.) ● Apply NoSQL data modeling from application specific queries ● Use Atomic Aggregates and denormalization as data modelling techniques to optimize query processing Software to download: MongoDB Neo4j SAPIQ Cassandra In case you have a Mac / IOS operating system you will need to use a virtual Machine (VirtualBox, Vmware).
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Este curso aborda os fundamentos do BigQuery para profissionais que já conhecem data warehouses em nuvem baseados em SQL no Redshift e querem começar a trabalhar no BigQuery. Com conteúdo interativo e laboratórios práticos, você vai aprender a provisionar recursos, criar e compartilhar recursos de dados, ingerir dados e otimizar a performance de consultas no BigQuery. Com base no seu conhecimento do Redshift, você também aprende sobre as semelhanças e diferenças entre o Redshift e o BigQuery para começar a usar data warehouses no BigQuery.
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