The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Pearson
Cisco Software-Defined Wan for Enterprise & Cloud: Unit 3
This course covers advanced routing techniques, high availability strategies, and policy configurations in SD-WAN. You'll learn the Overlay Management Protocol (OMP) to manage routes like static, OSPF, EIGRP, and BGP, with practical examples. You'll study high availability with TLOC extensions and redundancy protocols like VRRP and HSRP for strong network performance. You'll also cover SD-WAN policies, including access control lists and multi-regional topologies, and implementing application-aware routing for effective traffic management. By the end, you'll be able to design, deploy, and manage complex SD-WAN environments.
Universidades Anáhuac
Análisis de datos empresariales con R
Si tomas decisiones en tu empresa o deseas involucrarte en la ciencia de datos y el uso de tecnologías computacionales, este curso es para ti. El análisis multivariado es muy importante y único, al tomar en cuenta al mismo tiempo las diferentes variables a las que está sujeta una entidad, la cual puede ser numérica o categórica, es decir, podemos analizar tanto datos que representan propiedades físicas o químicas, como datos que que son indicadores de una situación o estado. De esta forma podemos analizar cualquier tipo de información proveniente de nuestra empresa y ser capaces de tomar mejores decisiones al considerar todos los factores que afectan a nuestro elemento en cuestión. Y esta es la parte que casi iguala la capacidad de nuestro cerebro de poder decidir de forma casi instantánea y ponderar todas las variables involucradas en la toma de una decisión que puede ser de vida o muerte. Cada vez que manejamos sometemos a nuestro cerebro a un continuo análisis multivariado que pondera variables como la velocidad, las condiciones del clima, del camino, las distracciones internas y externas o los imprevistos que pudiéramos encontrar. Esto es lo que hacemos en el análisis multivariado, considerar muchas variables, discriminarlas, agruparlas, relacionarlas y conformar grupos de datos. A lo largo de este curso, aprenderás las principales técnicas del análisis multivariante empleando R y R studio como herramienta de análisis, graficación y toma de decisiones. El software R de análisis estadístico y la plataforma de desarrollo R studio poseen la gran ventaja de ser de uso libre, con una gran comunidad de programadores que la enriquecen con librerías que hacen su uso sencillo y extremadamente poderoso. En este curso, además de aprender los fundamentos de R y R studio, aplicaremos las técnicas de análisis multivariado como: componentes principales, análisis de clústeres y análisis discriminante en la solución de problemas y casos empresariales. No necesitas experiencia previa en programación solo conocimientos básicos de estadística, te guiaremos paso a paso en el uso de de estas herramientas y su aplicación.
Coursera
Best Practices for Marketing with Facebook Messenger
By the end of this project, you will have a better understanding of how you can utilize Facebook Messenger as a strategic tool in your marketing efforts. Facebook Messenger is a free instant messaging platform for content sharing which includes photos, messages, event details, and even group chats. Upon completing this course, you will be able to create your own Facebook Business Page with Messenger and you will have a solid understanding of the various ways the Messenger platform can be used to help increase sales and develop deeper relationships with prospective customers/clients. 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.
University of Geneva
International Water Law
In recent decades, international law has undergone a series of major developments in order to accommodate the many new facets of freshwater management and protection. The adoption of universal, regional and basin instruments highlights how important it is to study the evolution of international water regulations and to be able to identify the main principles in this field. This course aims to provide the necessary background to understand and examine the regulation applicable to transboundary freshwaters especially to rivers, lakes and aquifers. It presents the principles and legal standards that govern the use, sharing, management and protection of these resources. The MOOC is made up of 5 modules. As each module addresses a different theme, they can be viewed in any order. However, the modules do follow a certain pedagogical logic and following in order will be especially helpful to those who are new to the subject. Each module is accompanied by an evaluation questionnaire or quiz. A certificate will be awarded to students who obtain an average of at least 80% in the quizzes. By the end of this course, you will be able to: 1) Describe the issues related to the regulation of transboundary freshwaters; 2) Explain how transboundary freshwater regulations have evolved; 3) Recall and interpret the key principles governing water resource regulation; 4) Understand the role of transboundary freshwater dispute settlement mechanisms in the development of international freshwater law (or to understand the role of international courts and tribunals in the resolution of conflicts) This MOOC was developed by the Platform for International Freshwater Law that is part of the Geneva Water Hub, assisted by the MOOC Team of the University of Geneva. Alongside the researchers and teachers of the Platform, several international experts have also participated. This MOOC is one of three courses supported by the Water Hub Geneva and the University of Geneva. The other MOOCS are "Water Management and Policy" (www.coursera.org/learn/gestioneau) and "Ecosystem Services: a method for sustainable development "(www.coursera.org/learn/ecosystem-services). The Global Water Program of the Swiss Agency for Development and Cooperation (SDC) has funded this course. This MOOC was originally created in French. It has English subtitles.
EDUCBA
Create & Deploy Company Websites Using Apache & PHP
By the end of this course, learners will be able to configure an Apache-powered development environment, create modular PHP components, design structured content pages, and evaluate a fully functional company website. This hands-on project-based course guides learners step-by-step through building a complete website using XAMPP, Apache, PHP, and reusable layout elements. Learners benefit by gaining real-world web development experience—starting from server setup and progressing through foundational components such as headers, footers, and homepage design, before advancing to essential pages like About, Services, and Contact. Each lesson teaches practical skills that can be directly applied in professional web development projects or portfolio-building exercises. What makes this course unique is its clear modular structure, focus on best practices, and complete start-to-finish project execution. Instead of teaching isolated concepts, the course immerses learners in the entire workflow of crafting a company website, reinforcing learning through structured practice quizzes and graded assessments. Whether you're new to web development or strengthening existing skills, this course provides a comprehensive, SEO-friendly, industry-aligned roadmap to mastering Apache-based website creation.
Pearson
Java SE 17 Developer (1Z0-829): Unit 6
Enhance your Java development skills with our specialized online course focused on mastering the Java Platform Module System. This course is meticulously crafted to guide you through the complexities of grouping, packaging, and deploying Java code using the module system. You'll learn to define modules and their dependencies, ensuring seamless integration and interaction between different parts of your application. Our lessons cover essential command-line operations for compiling and executing modular programs, highlighting the differences from non-modular systems. You'll gain insights into writing modular code, making your modules accessible, and controlling reflection capabilities. Additionally, the course delves into defining and using services, as well as the intricacies of project migration using unnamed and automatic modules. By the end of this course, you'll be proficient in producing modular and non-modular JARs, creating runtime images, and leveraging the full potential of the Java module system to build scalable and maintainable applications.
Illinois Tech
Operating System Virtualization - Bachelor's
Each successful student in this course will become familiar with hypervisors, virtualization terms, infrastructure considerations, and appropriate use cases. While designed to give an overview of today’s Virtualization technologies and methods, students in the course will gain enough practical knowledge to begin deploying various hypervisors and virtual machine environments using current industry standard platforms. Required Textbook: Various handouts will be provided Other Required Materials: Laptop with 8GB or Higher RAM, quad-core or higher CPU, HDD with 300-500GB Software Requirements: Oracle Virtual Box, Various hypervisors downloaded from the internet
Johns Hopkins University
Advanced Linear Models for Data Science 1: Least Squares
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models.
University of Geneva
Supervision du raisonnement clinique
Si vous supervisez des étudiants, des stagiaires en clinique, ou encore des internes en formation post graduée, ce MOOC sur la supervision du raisonnement clinique en contexte de soins est pour vous ! Vous y trouverez une modélisation du raisonnement clinique, ainsi que des outils concrets et efficaces pour superviser. Vous y découvrirez aussi comment identifier les difficultés de raisonnement clinique, et comment les corriger. Ce MOOC a pour objectif de vous soutenir dans le développement de vos compétences pédagogiques ! A l'aide de nombreuses vidéos, nous vous proposons des exemples de supervisions, ainsi que des démonstrations de méthodes et stratégies. Vous trouverez également de nombreuses ressources avec des articles ciblés qui vous aideront à poursuivre votre démarche de formation.
Google Cloud
Getting Started with Terraform for Google Cloud
This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
Vanderbilt University
Generative AI for HR Professionals
Imagine spending your days having meaningful conversations with employees instead of drowning in paperwork. Picture yourself providing truly personalized career guidance instead of rushing through generic development plans. Envision leading strategic initiatives that transform your workplace culture rather than being buried under administrative tasks. This is the promise of AI augmentation - not replacing human judgment, but amplifying your capacity to do the work that only humans can do well. You weren't hired to be a document processor or form filler. You were hired to understand people, solve complex human problems, and create environments where everyone can thrive. But too often, the administrative burden of HR work steals time from these higher-value activities. This course teaches you to use AI as a force multiplier that gives you entirely new capabilities. You'll be able to analyze complex situations from multiple perspectives simultaneously, create personalized solutions at scale, and tackle challenges that would be impossible to handle manually. AI doesn't just handle your routine work - it expands what you can accomplish, letting you provide deeper insights, more comprehensive analysis, and truly customized support while still having time for the face-to-face interactions and strategic thinking that drive real organizational change. What You'll Master: These aren't theoretical concepts - they're practical prompting patterns that will immediately free up hours of your time every week while improving the quality of everything you produce. The Accessible Explanation Pattern: Transform dense technical jargon into crystal-clear insights. Never again struggle to understand complex resumes, job descriptions, or technical documents. Make any expert-level content accessible to your level of understanding. The Transformer Pattern: Take one piece of information and instantly reshape it into multiple formats. Turn performance reviews into timelines, emails, and action plans. Transform policies into clear communications for different audiences. The Question Generator Pattern: Never walk into an interview or meeting unprepared again. Generate targeted, insightful questions that reveal exactly what you need to know about candidates, policies, or situations. The Fusion with Citations Pattern: Combine information from multiple sources while maintaining complete traceability. Create comprehensive reports that you can confidently stand behind with proper documentation. The Standardization Pattern: Compare apples to apples even when dealing with completely different formats. Evaluate candidates fairly by extracting and organizing their qualifications in consistent, comparable ways. The Persona Pattern: See through other people's eyes before they even respond. Anticipate reactions, questions, and concerns from different employee groups to craft better policies and communications. Real-World Applications That Will Amaze Your Colleagues Performance Reviews: Fuse feedback from multiple sources into comprehensive evaluations with full citation trails. Create personalized development plans that account for individual backgrounds and company training catalogs. Hiring Excellence: Transform incomprehensible technical resumes into interview questions tailored to specific roles and candidates. Create standardized comparison frameworks that ensure fair evaluation. Policy Communication: Use virtual focus groups to anticipate employee reactions before rollout. Transform complex policies into clear, stress-reducing communications for different audiences. Document Intelligence: Extract key information from lengthy policies to answer specific questions with direct quotations and page references. Filter documents to show only relevant sections for decision-making. Dynamic Planning: Create professional development trajectories that update automatically as employees progress. Predict resource availability and capacity based on training completion rates. Most people use AI like a better search engine. You'll use it like having a team of expert consultants who handle all the administrative heavy lifting while you focus on what humans do best - building relationships, making nuanced decisions, and creating personalized solutions. You'll learn not just what to ask AI, but how to structure conversations that build on themselves, creating increasingly sophisticated outputs that would take you hours to produce manually. You'll transform from someone who processes information to someone who orchestrates intelligence, freeing yourself to spend more time on strategic thinking, one-on-one employee development, and the complex interpersonal work that drives organizational success. Who This Course Is For: HR professionals who want to reclaim their time for meaningful human interaction and strategic work. People who are tired of being buried under administrative tasks and want to focus on personalized employee support and organizational development. No technical background required. No programming needed. Just the willingness to learn patterns that will give you back hours every week to focus on the work that truly matters.
Edureka
Machine Learning and NLP Basics
The Machine Learning and NLP Basics course is a learning resource designed for individuals interested in developing foundational knowledge of machine learning (ML) and natural language processing (NLP). This course is ideal for students, data scientists, software engineers, and anyone seeking to build or strengthen their skills in machine learning and natural language processing. Whether you are starting your journey or seeking to reinforce your foundation, this course provides practical skills and real-world applications. Throughout this course, participants will gain a solid understanding of machine learning fundamentals, explore various ML types, work with classification and regression techniques, and engage in practical assessments. By the end of this course, you will be able to: - Understand and apply core concepts of machine learning and NLP. - Differentiate between various types of machine learning and when to use them. - Implement classification, regression, and optimization techniques in ML. - Utilize deep learning models for complex problem-solving. - Navigate TensorFlow for building and training models. - Explore CNNs and RNNs for image and sequence data processing. - Explore NLP techniques for text analysis and classification. Learners are expected to have a basic understanding of programming. Familiarity with Python and AI fundamentals is helpful but not required. It is designed to equip learners with the skills and confidence necessary to navigate the evolving landscape of AI and data science, laying a strong foundation for further learning and professional growth.
University of Michigan
Accounting for Decision Making
Through this course, you will start by addressing the two “big questions” of accounting: “What do I have?” and “How did I do over time?” You will see how the two key financial statements – the balance sheet and the income statement - are designed to answer these questions and then move on to consider how individual transactions aggregate to make up these financial statements. After developing a broad understanding of accounting and financial statements, you will begin to develop a more nuanced understanding of individual components of doing business, such as making a sale or building inventory. By considering many of the more common actions of a company, you will build your understanding of accounting, and explore these concepts by applying them across various types of transactions. Once you understand these individual concepts better, you will be ready to return to the overall financial statements and use them as informational tools, including building ratios. You can do this course standalone or to qualify for the residential component of the Finance for Strategic Decision-Making Executive Education program. For more information, see the FAQ below.
Universidad de los Andes
Estilos de Liderazgo: opciones para avanzar en desafíos complejos
Liderazgo es una palabra que se usa para muchas cosas diferentes y a veces opuestas. Cuando la gente intenta concertar una definición, hay una tendencia general a recurrir al modelo heroico del liderazgo, de un hombre con características especiales y en un puesto directivo que convence a otros de seguirlo hacia su visión. Este modelo es atractivo, pero limitado y obsoleto para la mayoría de los desafíos que nos importan hoy en día. El “modelo heroico” suele ser muy útil para solucionar problemas que no requieren cambios en las personas involucradas en solucionarlos, pero es menos útil o incluso factible para progresar en la solución de problemas difíciles de definir, en situaciones en que hay mucha incertidumbre, y cuando parte importante del problema son las decisiones hábitos y miedos de la propia gente (tú incluida/o) que necesita trabajar para llegar a la solución. En este curso vamos a preguntarnos ¿qué concepción de liderazgo y qué tipo de habilidades son útiles para el complejo y cambiante mundo en el que vivimos?, ¿cómo se aprenden estas habilidades?, ¿para qué tipo de desafíos es necesario el liderazgo?, ¿qué recursos de poder y formas de autoridad hacen parte del liderazgo y cuáles no?, ¿qué riesgos tiene la práctica del liderazgo?, ¿cómo te proteges?. Vamos a invitarte a que, en el espacio virtual y en tu vida real, adquieras una perspectiva potente, unas “Gafas Efectivas” para mirar el mundo complejo en el que vives, diagnosticar los desafíos que te importan y planear intervenciones para avanzar en ellos. En otras palabras, el curso te acompaña en el proceso de adueñarte de una metodología de diagnóstico e intervención, que llamamos Espiral de Liderazgo Consciente, que te va ayudar a identificar y caracterizar: 1. Tus propósitos 2. Los desafíos y oportunidades que enfrentas para llegar a ellos 3. Los aspectos técnicos de estos desafíos/oportunidades, que tienen que ver con reglas, dinero, conocimiento, expertos y autoridades formales 4. Los aspectos humanos y sistémicos de estos desafíos/oportunidades: que tienen que ver con las personas interesadas y afectadas, sus valores, miedos, las facciones que forman y a veces pelean entre sí, la probabilidad de que sean aliados o detractores 5. Tus recursos formales e informales (y desafíos internos) que afectan el tema que quieres avanzar, y los riesgos del liderazgo que probablemente enfrentarás Todo ello para que planees intervenciones y experimentos de avance, y reflexiones sobre cómo protegerte (pensando en el sistema, haciendo alianzas, reflexionando en la acción, escuchando a las facciones, gestionando tus emociones, etc) Vamos a invitarte también a observar y profundizar tu habilidad para estar presente y para reflexionar y aprender antes, durante y después de hacer alguna intervención dirigida a mejorar tus resultados personales o de grupo. En otras palabras, vamos a acompañarte a profundizar en tres herramientas que llamamos “Estoy Aquí”; “Subir al Balcón” y “Parada para respirar” que tienen que ver con meta-observar al mundo, a ti mismo en el mundo y a tu mundo interior y encontrar la respuesta a preguntas como: ¿cómo te sientes cuando estás intensamente presente en una actividad (o en un sistema en el que quieres intervenir para cambiar los resultados)?, ¿cuáles son los mecanismos por los que se dispersa tu atención y las justificaciones que te das a ti mismo para dejar de estar presente?, ¿qué está pasando en el mundo externo?, ¿qué está pasando en tu interior?. Estos objetivos de aprendizaje implican que el curso al que vas a entrar no está diseñado de forma convencional, como clases magistrales en las que un experto te “enseña” conceptos, sino que el rol de los profesores en este curso es el de diseñar oportunidades de aprendizaje para ti, y acompañarte a que reflexiones sobre ellas. "Estilos de Liderazgo: Opciones para Avanzar en Desafíos Complejos" (https://www.coursera.org/learn/estilos-liderazgo/home/welcome) es el primero de cuatro cursos que componen el programa especializado en "Liderazgo Efectivo para el Siglo XXI" (https://www.coursera.org/specializations/liderazgo-efectivo). Los otros tres cursos son: "Autoliderazgo y Gestión de Emociones para Avanzar en Desafíos Complejos"; "Comunicación, Experimentación y Aprendizaje en Liderazgo"; y "Liderazgo para el siglo XXI". Puedes tomar todos los cursos por separado o sólo uno de ellos, sin embargo te recomendamos que te inscribas y participes en los cuatro, ojalá en el orden que te proponemos. En general, todo el programa está dirigido a cualquier persona interesada en conectarse con sus propósitos y profundizar sus habilidades para progresar en desafíos personales y colectivos muy complejos. Es especialmente útil para personas en mandos medios y altos en organizaciones públicas, privadas y no gubernamentales (ONGs). También para líderes comunitarios, activistas y en general gente que trabaja con personas y que necesita desarrollar o profundizar habilidades y herramientas para crear, a partir de grupos con opiniones e intereses diversos comunidades que trabajan juntas para avanzar en los temas que les importan. Va a ser útil, también, para personas interesadas en aprender a mejorar los resultados que observan en su esfera de vida más personal.
University of Colorado Boulder
Introduction to Computer Vision
Introduction to Computer Vision guides learners through the essential algorithms and methods to help computers 'see' and interpret visual data. You will first learn the core concepts and techniques that have been traditionally used to analyze images. Then, you will learn modern deep learning methods, such as neural networks and specific models designed for image recognition, and how it can be used to perform more complex tasks like object detection and image segmentation. Additionally, you will learn the creation and impact of AI-generated images and videos, exploring the ethical considerations of such technology. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Packt
Introduction to RNN and DNN
Artificial Intelligence is transforming industries by enabling machines to learn from data and make intelligent decisions. This course offers an in-depth exploration of Recurrent Neural Networks (RNN) and Deep Neural Networks (DNN), two pivotal AI technologies. You’ll start with the basics of RNNs and their applications, followed by an examination of DNNs, including their architecture and implementation using PyTorch. You will master building and deploying sophisticated AI models, develop RNN models for tasks like speech recognition and machine translation, understand and implement DNN architectures, and utilize PyTorch for model building and optimization. By the end, you'll have a robust knowledge of RNNs and DNNs and the confidence to apply these techniques in real-world scenarios. Designed for data scientists, machine learning engineers, and AI enthusiasts with basic programming (preferably Python) and statistics knowledge, this course combines theory with practical application through video lectures, hands-on exercises, and real-world examples.