The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Packt
Continuous Integration Mastery with Jenkins
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Master Continuous Integration (CI) using Jenkins with this comprehensive course. Through hands-on labs and deep dives into CI pipeline setups, you will learn how to streamline the development lifecycle by automating key processes. By the end of this course, you'll be equipped with the skills to build, manage, and optimize CI pipelines for your projects. You will start by setting up a Jenkins server and environment, followed by building and configuring your first CI pipeline manually. As you progress, you’ll explore advanced features like multi-branch pipelines, declarative Jenkinsfiles, and integration with version control systems like Git. The course also includes critical concepts such as enforcing Git-based workflows, managing code reviews, and applying trunk-based development models for seamless CI integration. The course further dives into container-based delivery systems by teaching how to integrate Jenkins with Docker. You'll get hands-on experience setting up Docker agents for your Jenkins pipelines, writing Dockerfiles, and automating the building and publishing of Docker images. You'll learn how to optimize image sizes for faster deployments by utilizing multi-stage Docker builds. This course is perfect for developers and DevOps engineers who want to enhance their skills in automating CI/CD processes with Jenkins. No prior Jenkins experience is necessary, but familiarity with Git and basic coding concepts will be beneficial. Whether you're a beginner or someone looking to sharpen your CI skills, this course will take you from foundational principles to advanced integration techniques.
Coursera
Deploying and Maintaining Production AI Systems
Most machine learning models fail in production not due to poor algorithms, but from inadequate deployment practices, unmonitored performance drift, and missing operational safeguards. This course equips you with the MLOps and site reliability engineering skills to deploy generative AI systems safely, automate model lifecycle management, and maintain peak performance in production environments. You will learn to orchestrate deployment workflows with canary releases and automated rollbacks, implement CI/CD pipelines with compliance checks and drift-triggered retraining, and design observability systems using logs, metrics, and tracing. Through hands-on projects, you will create performance dashboards that connect user experience with operational KPIs and build automation pipelines that improve reliability without sacrificing speed. These practical skills prepare you for roles as MLOps engineers, AI deployment specialists, and site reliability engineers. By the end of this course, you will be able to make data-driven release decisions, reduce downtime through proactive monitoring, and implement robust operational practices for AI systems at scale.
Whizlabs
Azure ML: Designing and Preparing Machine Learning Solutions
Welcome to the Azure ML: Designing and Preparing Machine Learning Solutions This course is designed to provide a comprehensive foundation in data science and machine learning, equipping learners with essential knowledge of key ML principles, data management, and real-world applications. Participants will explore managing machine learning environments and data workflows in Azure, gaining hands-on expertise in Azure Data Factory, Synapse Analytics, and Azure ML SDK (v2) to streamline ML lifecycle operations. Additionally, the course covers designing end-to-end ML solutions and MLOps architectures, ensuring effective model deployment, monitoring, and retraining strategies using Apache Spark and scalable workflows. Learners will gain the ability to select optimal services and compute options, differentiate between real-time and batch model deployment, and organize Azure ML environments effectively. This course is divided into three modules, each containing structured lessons and video lectures to enhance understanding. Participants will engage with approximately 3:00–4:00 hours of video-based instruction, offering both theoretical insights and practical knowledge. To reinforce learning, graded and ungraded assignments are included within each module, allowing learners to assess their understanding and application of key concepts. Module 1: Get started with Microsoft Data Analytics Module 2: Prepare a machine learning solution Module 3: Design a Machine Learning Solution By the end of this course, you will be able to learn Understand the core concepts of data science, machine learning, and the role of a data scientist. Learn about different types of machine learning and their real-world applications. Explore key data aspects, common ML terminology, and statistical foundations essential for modeling. Gain insights into various machine learning models and how to select appropriate solutions. This Course is for Data Scientists, Data Analysts, ML Engineers, and ML Associates, those who were mainly working with the Microsoft Azure Cloud Platform
Google Cloud
BigQuery: Qwik Start - Command Line
This is a self-paced lab that takes place in the Google Cloud console. This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short videos Get Meaningful Insights with Google BigQuery and BigQuery: Qwik Start - Qwiklabs Preview.
IE Business School
Analizando las Políticas Económicas
Este curso utiliza un enfoque no técnico para analizar la forma en la que los gobiernos utilizan políticas económicas para influenciar la economía de sus países. Al finalizar el curso el participante hablará con propiedad sobre temas tan importantes como la deuda y el déficit de los países, podrá examinar las políticas fiscales y monetarias así como las reformas estructurales de los países. Estos conceptos le ofrecerán los conocimientos necesarios para estar informados y poder crear su propio criterio respecto a los debates económicos de la actualidad: estímulos fiscales vs. austeridad, las virtudes de las innovaciones de los bancos centrales en política monetaria, cuándo se necesitan altas tasas de interés y el camino hacia el crecimiento para muchas de las economías más avanzadas.
Michigan State University
Getting Started With Music Theory
This course is a brief introduction to the elements of music theory for those with little or no music theory experience. We will explore pitch, rhythm, meter, notation, scales, keys, key signatures, meter signatures, triads, seventh chords, and basic harmony. If you listen to music or play music by ear, and you want to know more about how music is organized and notated, this course is for you. By the end of the course, you should know all major and minor keys, how to read and write in treble and bass clef using standard meters and rhythmic values, and how to notate and harmonize a simple melody. This course can serve as a stand-alone basic music theory course, or it can be a springboard to more advanced theory and composition courses. Your instructor is Bruce Taggart, Associate Professor of Music Theory at Michigan State University, in the College of Music, where he has taught undergraduate and graduate music theory since 1996.
Microsoft
Copilot Best Practices, Ethics and Regulatory Implications
Equip yourself with the knowledge and tools needed to responsibly leverage Microsoft Copilot while navigating the complex landscape of ethical considerations and regulatory compliance. You’lll gain a comprehensive understanding of key ethical concepts relevant to generative AI, such as transparency, human oversight, accountability, and fairness. The course will delve into real-world scenarios, evaluating the effectiveness of various Copilot prompts and configurations through the lens of ethics and regulation. After completing this course, you'll be able to: • Identify key ethical and regulatory concepts related to generative AI, such as transparency, human agency and oversight, accountability, technical robustness and safety, diversity, nondiscrimination and fairness, privacy and data governance, and social and environmental well-being. • Evaluate the effectiveness of various Copilot prompts and configurations, while considering ethical implications and regulatory compliance in different usage scenarios. • Develop a comprehensive framework for responsible Copilot use incorporating best practices, ethical considerations, and adherence to relevant regulations. Required Course Materials: A Copilot license is required to complete this course. If you don’t have a Microsoft 365 Personal or Family license, you can start a free 30-day trial using the link provided in the course.
Capitals Coalition
Valorizar a natureza e pessoas para melhor tomada de decisão
The aim of the course is to introduce businesses employees to the Capitals Approach and help them to get started with integrating natural, social and human capitals into business decision-making. This course is an introductory course; no prior knowledge of natural, human or social capital is needed. The course provides a comprehensive introduction to the capitals approach and to undertaking a natural capital assessment, and is available for all employees and leaders, sustainability practitioners, procurement officers, accountants, human resources, auditing, strategy, risk management and finance departments. The material is covered in good depth and will require time and commitment to learning. Due to its comprehensive character, the course may be less suited to C-level management. The course consists of four modules and its structure follows the internationally recognized Natural Capital Protocol and Social and Human Capital Protocols. The course features many business examples to demonstrate why and how other businesses have integrated natural, social & human capital impacts and dependencies into their decision-making and management practices. The first two modules guide learners through risks and opportunities related to nature, people and society; introduce the concept of a Capitals Approach and present the business case for undertaking an integrated capitals assessment. The third and fourth modules focus specifically on natural capital and how to get started with a natural capital assessment. These modules guide learners along the scoping stage and introduce students to measuring and valuing natural capital. By the end of the course, participants are expected to have learned about the different capitals, why it is essential to embed them into business decision-making, and how to get started with a capitals assessment. Future course specializations will build upon this introductory course, by providing additional content on social and human capital and allowing the learner to go more in depth with the content and application. This course has been developed by the Capitals Coalition, supported by We Value Nature, a collaboration between ICAEW, WBCSD, IUCN & Oppla, with the support of Nature^Squared.
University of Geneva
Ecosystem Services: a Method for Sustainable Development
Ecosystem services are a way of thinking about – and evaluating – the goods and services provided by nature that contribute to the well-being of humans. This MOOC will cover scientific (technical), economic, and socio-political dimensions of the concept through a mix of theory, case-studies, interviews with specialists and a serious-game. By the end of this course, our aim is to enable you to: • define the concept of ecosystem services, its principles and limitations • understand the key services associated with any ressource (e.g., fresh water) through readings and case-studies • appreciate the advantages and potential risks of monetising ecosystem services • appreciate the social dimensions (power issues, cultural biases) embedded within any method • integrate tactical advice on mainstreaming this approach into policy and standard government practices • Optional: learn how to map ecosystem services with GIS tools The session that runs May 29th- July 10th will be actively monitored by the instructors, and learners will have the opportunity to ask questions. This course was developed by instructors from the University of Geneva with the help of numerous researchers and input from the Geneva Water Hub and the Natural Capital Project. The course was financed by the University of Geneva, the Global Programme Water Initiatives of the Swiss Agency for Development and Cooperation (SDC), and the Luc Hoffmann Institute. This MOOC is supported by the Geneva Water Hub and the University of Geneva along with the MOOC in « Water Resources Management and Policy » (www.coursera.org/learn/water-management) and the one in « International Water Law » (www.coursera.org/learn/droit-eau). We look forward to you joining us!
Coursera
Introduction to Market Research
Embark on a journey through the realm of market research, where data uncovers stories and trends reveal opportunities. This short course is designed for professionals who aspire to master the craft of market research, enabling them to make informed business decisions. Whether you're a marketing professional, business owner, product manager, student, data analyst, sales specialist, or someone in the realm of advertising and PR, this course will equip you with a foundational understanding of market research methodologies and their practical applications. Dive into the art of identifying market trends and measuring customer preferences, all while honing your analytical skills. With a prerequisite of basic communication, computer skills, and an analytical mindset, this course is perfect for busy individuals seeking to enhance their market insight swiftly and efficiently. Get ready to transform data into strategy and elevate your business acumen in this course.
Northeastern University
Introduction to Domain Models
This course is a continuation of the Introduction to Software Development and Applications course. In this course, you will dive further into exploring software engineering techniques and their application to real-world business problems. Students who take this course will be equipped with practical design and programming techniques for the purpose of modeling significant business applications quickly. In this course you will learn about constructing domain models. You will also refine your skills to employ systems thinking, the object-oriented paradigm, the visual programming technique, as well as productivity tools to put together complicated, powerful designs. We will practice simple and smart ways of making software programming enjoyable.
Johns Hopkins University
Fundamental Neuroscience for Neuroimaging
Neuroimaging methods are used with increasing frequency in clinical practice and basic research. Designed for students and professionals, this course will introduce the basic principles of neuroimaging methods as applied to human subjects research and introduce the neuroscience concepts and terminology necessary for a basic understanding of neuroimaging applications. Topics include the history of neuroimaging, an introduction to neuroimaging physics and image formation, as well as an overview of different neuroimaging applications, including functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, perfusion imaging, and positron emission tomography imaging. Each will be reviewed in the context of their specific methods, source of signal, goals, and limitations. The course will also introduce basic neuroscience concepts necessary to understand the implementation of neuroimaging methods, including structural and functional human neuroanatomy, cognitive domains, and experimental design.
Packt
AWS Data Collection and Storage
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course is designed to guide you through the essential AWS services for data collection and storage. You'll begin with in-depth exploration of data streaming using Amazon Kinesis. Learn to handle data producers and consumers, set up Kinesis Data Firehose, and integrate CloudWatch filters, all while gaining hands-on experience with real-time data ingestion. Practical exercises will help you understand key scaling and security features, ensuring that your data streams are managed efficiently. Next, you will focus on AWS storage solutions with a strong emphasis on Amazon S3. Explore storage classes, replication, versioning, and lifecycle policies, all critical to effective data management. Through hands-on labs, you’ll configure S3 buckets, implement encryption, and set up event notifications, providing you with the skills needed to manage vast amounts of data securely. DynamoDB services will be introduced for scalable data storage solutions, with hands-on practice in setting up databases and optimizing throughput for performance. By the end of this course, you’ll be able to create and maintain complex data pipelines, ensuring both scalability and security. You'll have the confidence to manage data at scale, implement efficient storage solutions, and optimize performance using AWS best practices, positioning yourself to handle any data challenges AWS environments may present. This course is ideal for data engineers, IT professionals, and AWS users who want to specialize in data collection and storage. Basic knowledge of AWS services is recommended, but no prior certification is required.
Universitat Politècnica de València
FlashDiet: Aprende como comer sano
La evidencia científica es abrumadora: una dieta balanceada es crucial para la salud, ayudando a prolongar la esperanza de vida y a prevenir dolencias crónicas como la enfermedad cardiovascular, la diabetes y el sobrepeso. ¿Quieres dominar los principios de la nutrición para aplicar hábitos saludables? Este curso te proporcionará los fundamentos de la alimentación humana y la dieta óptima como clave para un bienestar duradero.
Starweaver
IoT Based System Design: Foundations and Applications
IoT-Based System Design: Foundations and Applications is a comprehensive course designed to provide learners with a solid understanding of Internet of Things (IoT) technologies and their practical applications. Through a combination of theoretical learning and hands-on exercises, participants will explore the fundamental concepts, hardware components, software platforms, and real-world use cases of IoT systems. The course is structured to cater to learners ranging from beginners to those with intermediate-level knowledge in the field, offering a progressive learning experience that equips them with the skills needed to design, develop, and deploy IoT solutions across various industries. This course caters to a diverse audience, ranging from students pursuing degrees in computer science or engineering to professionals transitioning into IoT roles and entrepreneurs exploring innovative solutions. It is also suitable for technology enthusiasts eager to delve into the world of IoT and its practical applications. Whether you're a beginner looking to grasp the basics or an intermediate learner seeking to deepen your understanding and skills in IoT system design, this course provides a structured learning experience to accommodate your needs and aspirations in the field. To make the most of this course, participants should possess a basic understanding of computer science principles and fundamental programming concepts. Familiarity with electronics and networking fundamentals will also be beneficial. However, what matters most is a genuine interest in IoT technologies and their potential applications across various industries. Whether you're a student, a professional, or an enthusiast, this course provides the opportunity to develop the knowledge and skills needed to embark on a rewarding journey in IoT-based system design and development.
Google Cloud
Gemini in Google Sheets - Português Brasileiro
O Gemini para Google Workspace é um complemento que oferece aos clientes acesso a recursos de IA generativa na nossa plataforma. Neste minicurso, você vai conhecer as principais funcionalidades do Gemini e como elas podem ser usadas para melhorar a produtividade e a eficiência nas Planilhas Google.