12 053 cours
This is a self-paced lab that takes place in the Google Cloud console. In this hands-on lab we take a look through some of the information provided by the Cloud Monitoring tools, and teach some of the concepts you will need to know to take advantage of Cloud Monitoring effectively.
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This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to perform basic tasks in Cloud Storage using the Google Cloud Console. Watch the short video Google Cloud Storage: Massive Scalability Plus More.
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After completing this guided project, no matter if you are launching a new brand or want to optimize the social media strategy for an existing brand, you will be able to edit and improve your Facebook ads. The goal of this project is to get to know creative but yet simple ways to reach your target audience on Facebook. The objective of social media marketing is to find creative ways to attract the attention of users for its products and services, many times on a lean marketing budget. Today, you will first create a Facebook Business Page Account. Then, we will take a close look at different kinds of Facebook advertisements and analyze strategies of optimizing a Facebook advertisement. Your newly achieved skills will help you reach and grow your target audience when creating a new Facebook ad campaign in the future.
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Master absorption costing and overhead allocation with practical, real-world examples. Learn how to calculate accurate product costs and improve financial decision-making. This course is designed to help learners understand the fundamentals and applications of absorption costing in a simple and structured way. You will explore key concepts such as cost allocation, cost apportionment, overhead classification, and predetermined overhead absorption rates (POAR). Through step-by-step explanations and practical examples, learners will develop the ability to assign costs accurately, analyze production costs, and evaluate inventory valuation under absorption costing. By the end of this course, you will confidently apply cost accounting techniques in academic, professional, and business contexts. Whether you are preparing for exams or enhancing your accounting skills, this course provides a strong foundation in absorption costing and overhead management.
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Learn how to analyze investment asset classes, design portfolio allocation strategies, and apply financial planning techniques for effective wealth management and long-term financial security. This course provides practical skills in portfolio construction, risk management, retirement planning, and portfolio reporting using real-world investment tools and methodologies. The course begins with the foundations of investment and mutual funds, helping learners understand debt and equity asset classes, investment terminology, valuation concepts, risk-return relationships, and investor support systems. Learners will build a strong understanding of how different investment products contribute to portfolio performance. As the course progresses, learners focus on portfolio construction, fund selection, and strategic financial planning. The course explains how to align investments with financial goals through diversification, asset allocation, and structured investment decision-making. Advanced modules cover financial protection strategies, insurance planning, cash flow analysis, time value of money, fixed income instruments, retirement planning, and wealth management philosophies. Learners will also gain practical exposure to portfolio management systems, transaction processing, investment tracking, and reporting workflows. What makes this course unique is its end-to-end approach that combines portfolio management, financial planning, risk protection, and system-based implementation into one practical learning experience. By the end of the course, learners will be able to confidently build, analyze, manage, and optimize investment portfolios aligned with financial goals and risk profiles.
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"생성형 AI 애플리케이션은 대규모 언어 모델(LLM)이 발명되기 전에는 불가능에 가까웠던 새로운 사용자 경험을 만들 수 있습니다. 어떻게 하면 애플리케이션 개발자가 생성형 AI를 사용해 Google Cloud에서 강력한 대화형 앱을 빌드할 수 있을까요? 이 과정에서는 생성형 AI 애플리케이션에 대해 알아보고 프롬프트 설계 및 검색 증강 생성(RAG)을 사용해 LLM 기반의 강력한 애플리케이션을 빌드하는 방법을 학습합니다. 생성형 AI 애플리케이션에 사용할 수 있는 프로덕션 레디 아키텍처를 살펴보고 LLM 및 RAG 기반 채팅 애플리케이션을 빌드합니다."
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This course is geared towards anyone interested in learning about IBM, COBOL, mainframe computing, and the Software Development Lifecycle (SDLC) and increasing their knowledge and hands on experience with core concepts and technologies including life cycle and systems analysis concepts, design and structured coding, and a wide variety of topics designed to provide relevant, requisite working knowledge and practical experience.
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Gain a foundational understanding of key AI algorithms and build valuable skills highly sought after in tech and social impact fields. "Practical AI for Social Impact" introduces you to algorithms, including machine learning and reinforcement learning, with additional topics and resources referenced throughout the course. Crucially, this course also addresses special challenges in implementing AI for social impact. Throughout the course, we’ll discuss how to navigate data scarcity, bias, and ethical deployment in real-world communities. Case studies will explore potential scenarios with sequential, adaptive decisions, helping you approach new situations with tact and knowledge. By the end of the course, you’ll have developed skills highly sought after in tech and nonprofit sectors, empowering you to optimize resource distribution and drive systemic change at scale. This is the second course in the three-course series, "Realizing AI for Social Impact", where you will explore use cases and frameworks for deploying AI to achieve social impact.
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This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn the basic functionalities of Cloud Healthcare API using the Fast Healthcare Interoperability (FHIR) data model.
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How can businesses and investors help fill the multi-trillion-dollar gap needed for sustainable development? Simply put: by incorporating sustainability and social impact factors on people and planet into management decisions. Through this course, anyone can learn to improve their organization's practice of impact measurement and management and align their ESG or impact activities and reporting with emerging global standards. Impact Measurement and Management for the SDGs is a collaboration between UNDP SDG Impact and the award-winning team at CASE at Duke University. The United Nations Development Programme (UNDP) is a steward of the United Nations Sustainable Development Goals (SDGs) that were launched in 2015 and to which 193 countries have signed up to achieve by 2030. The SDGs are a shared plan to end extreme poverty, reduce inequality, and protect the planet; they have become the world’s blueprint to achieve a better and more sustainable future for all. But the public sector cannot meet those goals alone. Climate change, poverty, racial and gender equity, food, health, education, clean water − the list of challenges faced by people and planet is too long. Businesses and investors have stepped in to help. The course was designed around the fundamental elements of the SDG Impact Standards, the only management standards that embed sustainability at the core of an organization in the holistic way intended by the creators of the SDGs. The course demonstrates how the SDG Impact Standards help organizations align with responsible business principles, other standards, and best practices in impact management. In the course, you’ll learn to improve decision-making for positive impact on people and planet in line with the SDG Impact Standards and the Operating Principles for Impact Management. In the course, we have translated 4 universal practices of impact management into practical actions: SET STRATEGY, INTEGRATE, OPTIMIZE and REINFORCE. We teach the steps to implement these actions through short videos and lessons with concrete practical examples. Professionals who know how to apply these sustainable management standards are increasingly in demand by institutions globally as they work to improve their performance and reporting around ESG and impact management. If you work or wish to work within an enterprise, a corporation, a fund that manages assets or an asset owner or advisory that oversees investment assets, or if you just want to learn more about impact investing, ESG, social finance or corporate reporting, this course will help you master the core concepts and practices in impact management for the SDGs and other impacts from enterprise and investor perspectives. This course was written and is delivered by CASE Faculty Director Cathy Clark, and benefitted from extensive input from a larger team from UNDP, CASE, global academic advisors, and other experts. For a full list of acknowledgements, see: https://sites.duke.edu/casei3/for-practitioners/impact-measurement-and-management-for-the-sdgs-course/ Selected course materials have been translated into Baha Indonesia, Thai, and Vietnamese. Spanish and Turkish translations are coming soon. Please find links to these translations under the Resources tab once you are inside the course. This course was made possible by generous support from Norad.
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The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course. To successfully complete course assignments, students must have access to Microsoft Excel. ________________________________________ WEEK 1 Module 1: Basic Data Descriptors In this module you will get to understand, calculate and interpret various descriptive or summary measures of data. These descriptive measures summarize and present data using a few numbers. Appropriate Excel functions to do these calculations are introduced and demonstrated. Topics covered include: • Categories of descriptive data • Measures of central tendency, the mean, median, mode, and their interpretations and calculations • Measures of spread-in-data, the range, interquartile-range, standard deviation and variance • Box plots • Interpreting the standard deviation measure using the rule-of-thumb and Chebyshev’s theorem ________________________________________ WEEK 2 Module 2: Descriptive Measures of Association, Probability, and Statistical Distributions This module presents the covariance and correlation measures and their respective Excel functions. You get to understand the notion of causation versus correlation. The module then introduces the notion of probability and random variables and starts introducing statistical distributions. Topics covered include: • Measures of association, the covariance and correlation measures; causation versus correlation • Probability and random variables; discrete versus continuous data • Introduction to statistical distributions ________________________________________ WEEK 3 Module 3: The Normal Distribution This module introduces the Normal distribution and the Excel function to calculate probabilities and various outcomes from the distribution. Topics covered include: • Probability density function and area under the curve as a measure of probability • The Normal distribution (bell curve), NORM.DIST, NORM.INV functions in Excel ________________________________________ WEEK 4 Module 4: Working with Distributions, Normal, Binomial, Poisson In this module, you'll see various applications of the Normal distribution. You will also get introduced to the Binomial and Poisson distributions. The Central Limit Theorem is introduced and explained in the context of understanding sample data versus population data and the link between the two. Topics covered include: • Various applications of the Normal distribution • The Binomial and Poisson distributions • Sample versus population data; the Central Limit Theorem
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Les équipes ont beau avoir de bonnes intentions et de très bonnes idées, et travailler dur, elles finissent trop souvent par créer des produits dont personne ne veut, que personne ne peut utiliser et que personne n'achète. Mais ce n’est pas une fatalité. L’approche agile et le design thinking abordent le développement de produits selon une approche différente, et efficace, qui propose des solutions intéressantes à des problèmes significatifs. Dans ce cours, vous apprendrez à déterminer ce qui est attractif pour un utilisateur dès le début du processus, afin d’anticiper la valeur, en incitant votre équipe à composer des formulations testables sur l'utilisateur et en créant une perspective commune. Ce cours est soutenu par le Batten Institute de la Darden School of Business de l'université de Virginie. Le Batten Institute a pour mission d'améliorer le monde grâce à l'entrepreneuriat et à l'innovation : www.batteninstitute.org.
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