The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Google Cloud
프로덕션 머신러닝 시스템
이 과정에서는 프로덕션 환경에서 고성능 ML 시스템을 빌드하기 위한 구성요소와 권장사항을 자세히 살펴봅니다. 정적 학습, 동적 학습, 정적 추론, 동적 추론, 분산 TensorFlow, TPU 등 고성능 ML 시스템 빌드와 관련된 일반적인 고려사항을 다룹니다. 이 과정에서는 정확한 예측 능력 외에도 양질의 ML 시스템을 만드는 특성을 탐구하는 데 중점을 둡니다.
Universidad Nacional Autónoma de México
Control automático: La tecnología invisible
A lo largo de la historia, el ser humano se ha empeñado en construir dispositivos que le hagan más cómodo su día a día. Además, siempre ha estado interesado en que éstos lleven a cabo la tarea por sí mismos, sin necesidad de una supervisión continua. En nuestros días, muchos dispositivos llevan a cabo tareas como por arte de magia; pareciera que piensan o que adivinan nuestros deseos, que nunca se pueden equivocar o que su precisión y velocidad no puede ser superada. Los sistemas de control son una parte crucial de este funcionamiento. Con este curso, los participantes conocerán la aplicación de los sistemas de control y algunos ejemplos de ellos. Además, revisarán a grandes rasgos sus características básicas y sus diferentes representaciones, con especial énfasis en el modelado matemático. Al término del curso: Identificarás la utilidad y las características principales de los sistemas de control. Distinguirás entre un sistema de control en lazo abierto y un sistema de control en lazo cerrado.
Berklee
Proyecto final de Músico moderno
La industria de la música está experimentando enormes cambios, y como resultado de ello, los músicos necesitan cada vez más habilidades en un número de áreas diferentes para tener éxito. El programa especializado de Músico moderno está diseñado para proporcionarle una base de conocimientos sobre teoría musical, producción de música y composición de canciones, lo que le proporciona las herramientas que necesita para escribir y producir su propia música. Esta obra fue financiada con una donación del Banco Inter-Americano de Desarrollo con recursos del Fondo Coreano para la Reducción de la Pobreza. Las opiniones expresadas en esta obra son exclusivamente de los autores y no necesariamente reflejan el punto de vista del Banco Interamericano de Desarrollo, de su Directorio Ejecutivo ni de los países que representa. El Banco Interamericano de Desarrollo no garantiza la veracidad de la data incorporada en esta obra. Puedes cambiar el idioma en Coursera de inglés al español utilizando la página de ajustes de tu cuenta. Para cambiar los ajustes en tu cuenta de Coursera sigue los siguientes pasos: 1. Ve a coursera.org 2. En la esquina derecha superior haz click en el pequeño triángulo invertido que está a lado de tu nombre y foto. 3. Haz click en ‘Settings’. 4. Selecciona el recuadro debajo de ‘Language’ (idioma), selecciona español y salva los cambios realizados. Coursera ofrece ayuda financiera a los estudiantes que no pueden pagar los cursos y necesiten de una beca. Los estudiantes con ayuda financiera podrán tener acceso a todo el contenido del curso y completar todo el trabajo requerido para adquirir el Certificado de Coursera. La ayuda financiera solo aplica al curso en el que se aprobó la solicitud de ayuda financiera. Para aplicar haz click en la opción “Learn More and Apply” (aprende mas y aplica) debajo del menú a la izquierda.
University of Copenhagen
Academic Information Seeking
This course will introduce you to the basic elements of academic information seeking - we will explore the search process from defining a strategy to evaluating and documenting your search results. Attending the course will make you a proficient information seeker. You will learn how to carry out comprehensive literature searches based on your own research assignment. You will be guided through the various information seeking steps from selecting relevant search strategies and techniques to evaluating your search results, documenting your search process and citing your sources. Attending the course will enable you to: • Identify your information need • Evaluate databases and other information resources • Set up search strategies and use various search techniques • Formulate search strings based on your own research assignment • Identify relevant material types • Undertake critical evaluation of your sources • Search more efficiently on the internet • Avoid plagiarism • Cite correctly • Work with reference management • Document your search process The course is intended for undergraduate students but the lessons will be useful to anyone who is interested in becoming better at finding scientific information. There are no formal requirements for the course. The series consists of 21 lectures that are organized into three modules. The lectures include small assignments and quizzes (to check comprehension). The lectures will each touch upon a topic that is essential to the information seeking process. To get the most out of the lecture series, we recommend that you access the lectures while you are working on an academic paper. We also recommend that you watch the lectures in the order in which we have structured them. We recommend that you create and fill out a log book while attending the lectures. We have created a log book template that you can use during the course. The lecture series has been developed in collaboration between information specialists at University of Copenhagen and Technical University of Denmark
LearnQuest
Demand Forecasting Using Time Series
This course is the second in a specialization for Machine Learning for Supply Chain Fundamentals. In this course, we explore all aspects of time series, especially for demand prediction. We'll start by gaining a foothold in the basic concepts surrounding time series, including stationarity, trend (drift), cyclicality, and seasonality. Then, we'll spend some time analyzing correlation methods in relation to time series (autocorrelation). In the 2nd half of the course, we'll focus on methods for demand prediction using time series, such as autoregressive models. Finally, we'll conclude with a project, predicting demand using ARIMA models in Python.
Parsons School of Design, The New School
Aprovechar el Diseño para Detectar Oportunidades de Negocio
El objetivo de este curso es ayudarte a evaluar la importancia del diseño y la responsabilidad de los diseñadores. Examinará el papel cada vez mayor del diseño y las herramientas que lo ayudan a crecer. Analizaremos cómo los marcos de diseño pueden ayudar a encontrar oportunidades y enmarcar declaraciones de problemas. Finalmente, aprenderá a evaluar oportunidades, experiencias mediante el uso de un Lean Canvas. Para tener éxito en este curso, usted debe ser un profesional con al menos 2-3 años de experiencia en un entorno organizacional. Será útil tener experiencia específica en un puesto de diseño o trabajando con diseñadores. Al finalizar este curso, será capaz de: - Evaluar la importancia del diseño y las responsabilidades de los diseñadores - Examine el papel cada vez mayor del diseño y las herramientas que lo ayudan a crecer - Analizar cómo los marcos de diseño pueden ayudar a enmarcar las declaraciones de problemas e identificar oportunidades - Evaluar oportunidades, experiencias y el uso de un canvas
University of Virginia
Foundations of Business Strategy
Develop your ability to think strategically, analyze the competitive environment, and recommend firm positioning and value creation. In this course, developed at the Darden School of Business at the University of Virginia, top-ranked faculty will help you explore the underlying theory and frameworks that provide the foundations of a successful business strategy and provide the tools you need to understand that strategy: SWOT, Competitor, Environmental, Five Forces, and Capabilities Analyses, as well as Strategy Maps.
Universidad Austral
Finanzas para emprendedores
El objetivo de este curso es que seas capaz de analizar y relacionar los conceptos clave de las finanzas, de un modo sencillo y amigable, poniendo el foco en unir la estrategia del negocio con algunos pocos indicadores relevantes que te permitirán al final del curso, hacer un análisis y diagnóstico de la situación financiera de tu empresa. El curso cuenta con cuatro módulos en donde se combinarán videos explicativos con actividades para llevar a la realidad de la empresa cada uno de los conceptos. La propuesta final del curso es llevar a la práctica todos los conceptos. Por eso en el último módulo habrá un ejercicio de diagnóstico financiero. Para este curso inicial no es necesario que tengas conocimientos previos, dado que la estructura de los módulos te acompañará paso a paso con los contenidos necesarios, para comprender la situación financiera de un negocio y su rentabilidad.
Whizlabs
NVIDIA: Fundamentals of NLP and Transformers
NVIDIA: Fundamentals of NLP and Transformers Course is the third course of the Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course provides learners with foundational knowledge of Natural Language Processing (NLP) and practical skills for working with NLP pipelines and transformer models. It combines theoretical concepts with hands-on exercises to prepare learners for real-world NLP applications. This course covers key NLP topics, including tokenization, text preprocessing techniques, and word embeddings, along with the challenges of handling textual data. Learners will also explore sequence models (RNN, LSTM, GRU) and transformer architectures, gaining practical insights into self-attention mechanisms and encoder-decoder models. The course is structured into two modules, each comprising Lessons and Video Lectures. Learners will engage with approximately 3:00-3:30 hours of video content, covering both theoretical foundations and hands-on practice. Each module includes quizzes to reinforce learning and assess understanding. Course Modules: Module 1: Introduction to NLP: Concepts, Techniques, and Applications Module 2: Sequence Models and Transformers By the end of this course, a learner will be able to: - Understand NLP fundamentals, key tasks, and real-world applications. - Implement NLP techniques, including tokenization, word embeddings, and sequence models. - Explore transformer architecture, self-attention mechanisms, and encoder-decoder models. This course is intended for individuals interested in developing NLP expertise and working with transformer-based models. It is ideal for data scientists, machine learning engineers, and AI specialists seeking hands-on experience in modern NLP techniques.
Alfaisal University | KLD
مقدمة في علم الاقتصاد | Introduction to Economics
علم الاقتصاد (Economics) يتعلق بصورة مباشرة بحياة الإنسان، وسواء كان الإنسان منتجاً أو مستهلكاً أو مستثمراً أو من صنّاع القرار، فإنه يواجه دائماً قرارات اقتصادية مختلفة، متعلقة بحياته العملية أو الشخصية مما يجعل علم الاقتصاد (Economics) مهماً ومفيداً. تظهر الحاجة الماسة لعلم الاقتصاد (Economics) عندما يواجه الإنسان الموارد الإنتاجية النادرة أمام الاحتياجات المتعددة التي يواجهها، فعلم الاقتصاد (Economics) هو العلم الذي يهتم بدراسة الكيفية التي يتم فيها استخدام موارد إنتاج السلع والخدمات المختلفة. هذه الدورة هي دورة تمهيدية؛ فهي تلقي الضوء على أساسيات الموضوع بشكل عام بهدف التعريف به وبمحاوره الأساسية التي يجب الإلمام بها. إذا كنت من المهتمين بالاطلاع على مقدمة في الاقتصاد، أو كان مجال عملك يتطلب توظيف ذلك في سياق عملك، فهذه الدورة ستكون مثالية لإغناء خبرتك وتطوير مهاراتك بشكل فعال ومؤثر. حيث ستزودك هذه الدورة باطلاع واسع ودقيق على مجموعة من المحاور المتعلقة بهذا الموضوع، مثل: فهم كيفية الاستفادة من هذه المفاهيم في صنع القرارات المتعلقة بحياتك مثل قرارات الاستثمار أو الادخار وغيرها، التعرف على أهمية علم الاقتصاد للأفراد والدول، شرح العديد من المفاهيم الاقتصادية التي ستساعدك على التعرف على مبادئ علم الاقتصاد.
Google Cloud
Elastic Cloud Infrastructure: Scaling and Automation dalam bahasa Indonesia
Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk membuat interkoneksi jaringan yang aman, load balancing, penskalaan otomatis, otomatisasi infrastruktur, serta layanan terkelola.
ISC2
Network Security
Welcome to course 4 of 5 of this Specialization, Network Security. In this course, we will look at computer networking and securing the network. In today’s world, the internet connects nearly everyone and everything, and this is accomplished through networking. While most see computer networking as a positive, criminals routinely use the internet, and the networking protocols themselves, as weapons and tools to exploit vulnerabilities and for this reason we must do our best to secure the network. We will review the basic components of a network, threats and attacks to the network, and learn how to protect them from attackers. Network security itself can be a specialty career within cybersecurity; however, all information security professionals need to understand how networks operate and are exploited to better secure them. After completing this chapter, the participant will be able to: Explain the concepts of network security. - Recognize common networking terms and models. - Identify common protocols and ports and their secure counterparts. - Identify types of network (cyber) threats and attacks. - Discuss common tools used to identify and prevent threats. - Identify common data center terminology. - Recognize common cloud service terminology. - Identify secure network design terminology. - Practice the terminology of and review network security concepts. Agenda Course Introduction Module 1: Network Concepts and Models Module 2: Common Network Threats and Attacks Module 3: Network Security Infrastructure Module 4: Network Security Review This training is for IT professionals, career changers, college students, recent college graduates, advanced high school students and recent high school graduates looking to start their path toward cybersecurity leadership by taking the Certified in Cybersecurity entry-level exam. There are no prerequisites to take the training or the exam. It is recommended that candidates have basic Information Technology (IT) knowledge. No work experience in cybersecurity or formal education diploma/degree is required.
Johns Hopkins University
Statistical Inference
Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
Board Infinity
Transformers in Action: A Practical Approach to NLP and AI
"This intermediate-level course takes you beyond AI theory into the practical world of Natural Language Processing (NLP) powered by Transformer architectures. You’ll trace the evolution of language models—from traditional statistical methods and recurrent networks to attention-based systems like BERT, GPT, and T5—through engaging demos and real-world case studies. Across four modules, you’ll gain a deep understanding of how Transformers work, why they outperform previous models, and how to use them for NLP tasks such as classification, summarization, translation, and sentiment analysis. Through guided coding labs and hands-on exercises with Hugging Face tools, you’ll learn how to tokenize data, fine-tune pretrained models, evaluate results, and deploy applications efficiently. Whether you’re a developer, data scientist, or AI enthusiast, this course bridges the gap between concept and implementation—helping you turn complex architectures into tangible, working AI systems. By the end of this course, you will be able to: - Understand and explain how Transformer architectures process and generate human language. - Fine-tune and deploy pretrained models using Hugging Face tools and APIs. - Apply NLP techniques to real-world use cases such as summarization and classification. - Evaluate and interpret model performance using key metrics and visualizations. - Design and deliver an end-to-end NLP project, from training to deployment." Disclaimer: This is an independent educational resource created by Board Infinity for informational and educational purposes only. This course is not affiliated with, endorsed by, sponsored by, or officially associated with any company, organization, or certification body unless explicitly stated. The content provided is based on industry knowledge and best practices but does not constitute official training material for any specific employer or certification program. All company names, trademarks, service marks, and logos referenced are the property of their respective owners and are used solely for educational identification and comparison purposes.
Vanderbilt University
ChatGPT + Cybersecurity: AI-Powered Tabletops & Training
Struggling to prepare your team for unexpected cybersecurity threats? Imagine having an AI partner that can help you build hyper-realistic tabletop scenarios, practice decision-making under pressure, and uncover blind spots—all while saving time and resources. This course will guide you on a journey to revolutionize your approach to cybersecurity training by integrating ChatGPT into your tabletop exercises, ensuring your organization is ready for the real game. What You'll Learn: Create Dynamic and Realistic Cybersecurity Scenarios: Use ChatGPT to design interactive scenarios with branching decision trees. Craft exercises that adapt to participants’ choices, pushing them to think critically about complex challenges while uncovering new angles of attack. Perform Individualized, Targeted Practice with Micro-Tabletops: Learn how to use ChatGPT to create "micro-tabletops," small-scale exercises that allow individual team members or small groups to focus on their specific responsibilities and tools. These targeted simulations enable frequent practice, iterative hardening of specific domains (e.g., Active Directory or Okta), and integration with broader team exercises to ensure overall organizational preparedness. Master the Flipped Interaction Pattern for Training: Discover how to let AI take the lead in tabletop facilitation. This unique approach allows ChatGPT to simulate evolving incidents, ask probing questions, and dynamically adapt based on your team’s responses—making every session a tailored learning experience. Inject Real-World Pressure into Your Scenarios: Learn how to add authentic tension to decision-making exercises. With ChatGPT, you can create scenarios that mimic the real-world ripple effects of cybersecurity breaches, such as regulatory deadlines, stakeholder complaints, or operational disruptions. Optimize Your Team’s Response Through Iterative Practice: Transform the way your organization practices cybersecurity. Generate instant feedback, identify critical gaps, and refine responses—all in a fraction of the time and cost of traditional tabletop methods. Build Collaborative Decision-Making Skills Across Departments: Train technical, legal, and communications teams to coordinate effectively during crises. Use ChatGPT to highlight each group’s unique pressure points, ensuring all stakeholders are prepared for their roles in an incident response. Who Is This Course For? Cybersecurity Professionals: Overwhelmed by the time and cost of creating tabletops? Learn to streamline the process with AI. IT and Security Teams: Want to simulate realistic, high-pressure incidents? Use ChatGPT to craft exercises that build confidence and capability. Business Leaders and Decision Makers: Need to ensure your organization is ready for the unexpected? Gain insights into how AI can enhance readiness. Educators and Facilitators: Interested in teaching cybersecurity skills interactively? Master tools and techniques to engage participants in novel and impactful ways. Why Take This Course? Cybersecurity breaches are inevitable, but unpreparedness doesn’t have to be. With ChatGPT, you can democratize access to high-quality training, creating customized, realistic exercises that challenge your team to respond effectively. Whether simulating a phishing attack, addressing regulatory fallout, or handling complex stakeholder dynamics, this course empowers you to enhance your incident response capabilities. Imagine transforming your tabletops into immersive learning experiences—without the time, cost, and complexity of traditional methods. By the end of this course, you’ll have the skills to use generative AI for designing, facilitating, and iterating on exercises that keep your team sharp and ready for anything. Join the growing number of professionals revolutionizing cybersecurity readiness with AI. Don’t get caught unprepared—enroll today and start building stronger defenses with ChatGPT!
Google Cloud
Google Cloud 에서 데이터 레이크와 데이터 웨어하우스 빌드하기
데이터 레이크와 데이터 웨어하우스를 사용하는 기존 접근방식은 효과적일 수 있지만, 특히 대규모 엔터프라이즈 환경에서는 단점이 있습니다. 이 과정에서는 데이터 레이크하우스의 개념과 데이터 레이크하우스를 만드는 데 사용되는 Google Cloud 제품을 소개합니다. 레이크하우스 아키텍처는 개방형 표준 데이터 소스를 사용하며 데이터 레이크와 데이터 웨어하우스의 장점을 결합하여 많은 단점을 해결합니다.