The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Google Cloud
Google Cloud Fundamentals: Core Infrastructure em Português Brasileiro
Noções básicas do Google Cloud: Core Infrastructure" é uma apresentação da terminologia e de conceitos importantes para trabalhar com o Google Cloud. Usando vídeos e laboratórios práticos, o curso apresenta e compara vários serviços de armazenamento e computação do Google Cloud, além de ferramentas importantes para o gerenciamento de políticas e recursos.
Sciences Po
Cities are back in town : sociología urbana para un mundo globalizado
Acerca del curso Los procesos de globalización y europeización respaldan el rápido desarrollo de las ciudades en distintas partes del mundo. En el mundo contemporáneo, el proceso de urbanización está alcanzando un nuevo pico con el incremento de las megalópolis (más de 15 millones de habitantes) como Calcuta, Los Ángeles, Daca, El Cairo, Tokio, Nueva York, Shanghái, Ciudad de México. o Seúl. Más allá de las metrópolis modernas, los investigadores intentan entender estas grandes zonas urbanas con el uso de distintos conceptos, tales como "posmetrópolis", "ciudades globales" y "ciudades-regiones globales". La clase estudiará debates y modelos de ciencias sociales de ciudades y metrópolis, para así analizar y comparar los desarrollos actuales. ¿Cómo podemos estudiar dichas ciudades cuando se convierten en megalópolis? ¿El tamaño importa, y para qué? ¿Acaso vemos la creación de un mundo urbano extenso o, en cambio, vemos más allá de la convergencia aparente de procesos complejos de globalización comprendidos en relación con el capitalismo globalizado? ¿Es posible identificar las diferencias escondidas y el fortalecimiento de diversos mundos urbanos? ¿Cómo podemos lograr entender este mundo urbano cuando las ciudades no son unidades independientes, sino que tienen que compenetrarse en términos de territorio, instalación, y asimismo en materia de relaciones como el flujo, la movilidad y la circulación? ¿Cuál es la relevancia de los conceptos de las ciencias sociales desarrollados en el mundo occidental para poder analizar la transformación de Lagos? ¿Hasta qué punto puede el desarrollo sistemático de nuevas formas de comparación entre ciudades del norte y del sur cambiar las ciencias sociales y contribuir a superar el sesgo hacia la comparación nacional? Por el momento, y considerando las condiciones actuales del capitalismo, los asuntos políticos, económicos, culturales y sociales se convierten cada vez más en asuntos urbanos. En la concepción moderna del mundo, caracterizada por el tamaño, la construcción de viviendas, la división del trabajo diferenciada y la densidad de interacción, existen diferentes concepciones de ciudades que se han entremezclado y, a veces, hasta se han enfrentado. Dichas concepciones resaltan diferentes procesos de integración: el aspecto material de la ciudad, muros, plazas, viviendas, calles, iluminación, servicios públicos, edificios, desechos e infraestructura física; el aspecto cultural de la ciudad en términos de imaginación, diferencias, representaciones, ideas, símbolos, arte, textos, sentidos, religión y estética; los principios políticos y las políticas en materia de control, poder, gobierno, movilización, políticas públicas, bienes, educación; el aspecto social de la ciudad considerando los disturbios, las desigualdades étnicas, económicas y de género, la vida cotidiana y los movimientos sociales; y el aspecto económico de la ciudad: división del trabajo, escalas, producción, consumo, comercio, entre otros. Los asuntos urbanos clásicos sobre las desigualdades, viviendas, gobierno e integración, se relacionan con cuestiones referentes al tejido urbano, asuntos de movilidad e instalación, desarrollo sostenible y riesgos, creación de ciudades ciborg, problemas de control social y disturbios, cultura urbana, innovación y desarrollo económico urbano. Todos los vídeos realizados por Sciences Po para este MOOC están a cargo de Creative Commons (BY / NC / SA) Perfil recomendado El curso está diseñado para estudiantes de pregrado, pero también puede ser de interés para estudiantes de posgrado y profesionales en el sector de asuntos urbanos. Programa del curso : Semana 1: Introducción, definición, asuntos urbanos y el uso de modelos Semana 2: Ciudades europeas y el modelo weberiano de integración Semana 3: Ciudades coloniales y poscoloniales Semana 4: Ciudades industriales (y ciudades socialistas) y modelos marxistas Semana 5: Las metrópolis norteamericanas y la Escuela de Chicago Semana 6: Posmetrópolis, fragmentos y diferencias Semana 7: Ciudades globales y megaciudades Semana 8: Ciudades inteligentes y la sociología de la ciencia y la tecnología
Amazon Web Services
SageMaker Unified Studio Foundations for Data Analytics
***This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some courses have accessibility limitations and are working to address. If you require accommodation, please contact [AWS Training and Certification Customer Support](https://support.aws.amazon.com/#/contacts/aws-training).*** This course covers essential components of Amazon SageMaker Unified Studio, including its seamless interface for data analytics and AI tools, integration capabilities across SQL analytics, machine learning, and generative AI development, along with a deep understanding of the lakehouse architecture for unified data management. Students will also learn to implement robust data governance frameworks using Amazon SageMaker's built-in capabilities, ensuring secure and compliant data handling practices. Whether you're a data professional, analytics specialist, or AI developer, this course provides the practical knowledge needed to effectively leverage Amazon SageMaker's unified platform for modern data analytics and AI development workflows.
University of Michigan
Stocks and Bonds
In this course, we will apply the central concept and applications of Time Value of Money (TVM) to explore the structure and pricing of stocks and bonds at an introductory level. In this course, you will learn about bonds, different types of bonds (Zero Coupon bonds, Government bonds). You will learn about bond pricing calculations and see their direct connection to market data on bonds. You will also learn about stocks, and their pricing and valuation. You will learn about growth and dividend stocks and how to use market data. After completing this course, you will have an understanding of the two fundamental and pervasive ways in which savers transfer money to governments and corporations. You will be able to apply all this knowledge to personal investing decisions and, importantly, these same tools and frameworks are applicable to corporate decisions. This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization.
EC-Council
Digital Forensics Essentials: Hands-On Edition
The Digital Forensics Essentials (DFE) : Hands-On Edition course provides learners with the skills needed to conduct forensic investigations and analyze digital evidence. Learners will understand the fundamentals of computer forensics, identify and classify cybercrimes, and comprehend digital evidence and its forensic significance. The course covers the forensic investigation process, setting up a computer forensics lab, documenting the electronic crime scene, performing search and seizure, and preserving evidence. By the end of this course, learners will be able to analyze data, write investigation reports, and perform file system examination.
Microsoft
Excel and Copilot Fundamentals
This course introduces you to the basics of Microsoft Excel and its powerful Copilot feature, equipping you with essential skills for efficient data handling and analysis. You will learn to navigate Excel’s interface, apply fundamental formulas and functions, and develop prompt engineering techniques to leverage Excel Copilot for various tasks. By the end of this course, you will have a strong foundation in Excel, enabling you to perform basic data manipulations and utilize Copilot to streamline your workflow. By the end of the course, you’ll be able to: - Activate and effectively use Excel Copilot for basic tasks and queries. - Navigate the Excel interface and utilize basic features efficiently. - Apply fundamental Excel formulas and functions to perform calculations and data manipulation. - Develop basic prompt engineering skills for Excel Copilot. Tools you’ll use: - Microsoft Excel - Copilot in Excel 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.
Knowledge Accelerators
Excel Basics for Beginners: Workbooks, Formatting, Charts and Core Skills
Unlock the power of Excel—your gateway to smarter data management and analysis. • Microsoft Excel is the world’s most widely used spreadsheet tool, relied on by over 750 million users globally. Whether you're managing budgets, tracking inventory, or preparing reports, Excel is a must-have skill across industries. • Excel proficiency is one of the top 5 most requested skills in job postings across business, finance, and operations roles. Learning Excel basics boosts productivity and opens doors to data-driven decision-making. We help you get started quickly. Career Impact • Around 82% of business analyst roles require Excel • Entry-level professionals with Excel skills on average can earn up to 15% more (according to launch • Excel is foundational for careers in data, finance, and admin What You’ll Learn • Navigate the Excel interface and create workbooks • Organize, sort, and filter data using tables and formulas • Apply formatting and build charts to visualize insights What Makes This Course Unique ✅ Designed for true beginners—no prior Excel experience needed ✅ Bite-sized lessons with hands-on practice using real datasets ✅ Learn in just 90 minutes with focused, interactive modules ✅ Builds a foundation for advanced Excel and Power BI courses ✅ Includes downloadable practice files and auto-graded assignments Who Should Take This Course • Students and recent graduates building job-ready skills • Business professionals across roles in operations, sales, and support • Small business owners and retail managers • Anyone ready to start working with data confidently This course is intended as the first in a specialization of three courses—beginning with building basic data literacy skills in Excel and culminating with building data literacy in Power BI through our course "From Excel to Power BI." Start your Excel journey today and transform how you work with data—one cell at a time. *Please note: A Microsoft 365 subscription is required to access all features used in this course.*
Coursera
Cómo Configurar una Campaña en Facebook Ads
Al final de este proyecto, identificarás correctamente los objetivos de tus campañas de Facebook Ads utilizando la plataforma de Facebook Business Manager. A lo largo de las tareas, crearás campañas de alcance y de reproducciones de video para Facebook e Instagram, cargarás a la plataforma contenido en distintos formatos para ubicaciones como feed, stories, reels, y podrás identificar segmentaciones de audiencia específicas para llegar al público más indicado. Este proyecto guiado es para estudiantes intermedios que ya estén familiarizados con la plataforma de Facebook Business Manager, ya que desarrollaremos a partir de una cuenta ya creada. El estudiante deberá contar con un perfil personal de Facebook y con una cuenta de Facebook Business Manager previamente creada y asociada con dicho perfil personal. Asimismo, dentro de Business Manager, el estudiante deberá tener creada y configurada su cuenta publicitaria. El contenido de este proyecto comenzará a desarrollarse a partir de la pantalla de creación de campañas. Además, vamos trabajar a partir de conceptos de marketing básicos como embudo de ventas y ciclo de vida de un cliente. Es necesario comprender de manera detallada la estructura de una campaña de Facebook Ads para poder realizar anuncios de manera profesional, escalable y rentable. Facebook Ads es una herramienta muy poderosa que puede generar grandes retornos de inversión, siempre que realicemos una configuración correcta. Las campañas exitosas cuentan con una estructuración efectiva de objetivos, conjuntos de anuncios y formatos de anuncios, en donde cada componente está relacionado de manera estratégica.
Coursera
Solve Root Causes
Missed deadlines killing your team's momentum? This Short Course was created to help project management professionals accomplish systematic problem-solving that transforms recurring issues into lasting solutions. By completing this course, you'll be able to facilitate root-cause workshops that uncover the real reasons behind missed deadlines, document findings using fishbone diagrams in Asana, and build executable action plans that actually prevent issues from repeating. By the end of this course, you will be able to: Facilitate a root-cause workshop for repeated missed deadlines Capture fishbone diagram in Asana Build an action plan with tasks, owners, and milestones Track effectiveness over the next sprint This course is unique because it combines proven root-cause analysis techniques with practical Asana implementation, moving teams beyond symptom-fixing to address underlying delivery challenges. To be successful in this project, you should have a background in basic project management principles and Asana navigation.
Packt
Deep Learning with Keras and Practical Applications
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. Embark on a comprehensive journey into deep learning with Keras through this meticulously crafted course. The course begins with an engaging introduction to creating a multiclass classification model for assessing red wine quality. You'll learn to fetch, load, and prepare data, followed by exploratory data analysis (EDA) and visualization to uncover insights and patterns. As you progress, you'll delve into defining, compiling, fitting, and optimizing your model, ultimately using it for accurate wine quality predictions. Building on this foundation, the course transitions into the fascinating world of digital image processing. You'll explore the basics of digital images, followed by practical sessions on image processing using Keras functions. Advanced techniques such as image augmentation, both single image and directory-based, are covered in detail. The course also introduces Convolutional Neural Networks (CNNs), guiding you through model building, training, and optimization, specifically for flower image classification. The journey doesn't stop there. You'll venture into transfer learning with pre-trained models like VGG16 and VGG19, leveraging their power for enhanced model performance. Practical sessions on utilizing Google Colab's GPU for transfer learning ensure you gain hands-on experience in modern deep learning workflows. By the end of this course, you'll have a robust understanding of applying Keras to real-world problems, from data preprocessing to model deployment. This course is ideal for data scientists, machine learning engineers, and technical professionals with a basic understanding of Python programming and machine learning concepts. No prior experience with Keras is required, though familiarity with neural networks and deep learning frameworks will be beneficial.
Google Cloud
Pengantar Keamanan di Dunia AI
Kecerdasan Buatan (AI) menawarkan peluang melakukan perubahan transformatif, tetapi juga memunculkan tantangan keamanan baru. Kursus ini membekali para pemimpin keamanan dan perlindungan data dengan strategi untuk mengelola AI secara aman dalam organisasi mereka. Mempelajari framework untuk secara proaktif mengidentifikasi dan memitigasi risiko khusus AI, melindungi data sensitif, memastikan kepatuhan, dan membangun infrastruktur AI yang tangguh. Memilih kasus penggunaan dari empat industri berbeda untuk mengeksplorasi penerapan strategi ini dalam skenario dunia nyata.
Coursera
Segment and Validate Your Live Marketing Data
Did you know that nearly 40% of marketing data is wasted due to inaccurate audience targeting and unreliable tracking? Learning to segment and validate live data can turn that loss into actionable insight. This Short Course was created to help digital marketing professionals leverage analytics for data-driven decision-making, audience optimization, and reliable performance measurement in campaign management and website optimization. By completing this course, you will be able to segment, test, and verify live marketing data streams to uncover audience misalignments and ensure your campaign decisions are based on accurate, real-time insights—skills you can immediately apply to improve marketing performance. By the end of this 3-hour long course, you will be able to: • Apply audience segmentation techniques to analyze traffic and identify profile misalignments. • Evaluate real-time data fidelity by comparing against historical traffic patterns. This course is unique because it combines real-time marketing analytics with live data validation, helping you move beyond static reports to build continuous feedback loops that strengthen campaign accuracy and audience targeting. To be successful in this project, you should have: • Basic understanding of web analytics concepts • Familiarity with digital marketing metrics • Access to Google Analytics or a similar analytics platform
Coursera
Develop Linkedin designs with Visme
At the end of this project, you will have all the basic skills to create digital content for Linkedin using Visme, an online tool for designing and editing Marketing content. You will be able to discover in detail the different features of the platform, and will be able to create professional graphic content for LinkedIn. This project is for beginners, people who have never used Visme to create Linkedin content. It is ideal for those who would like to use Visme for their professional projects.
Google Cloud
Introduction to Google Workspace 日本語版
「Introduction to Google Workspace Administration」は、Google Workspace Administration シリーズの最初のコースです。 このシリーズは新たに Google Workspace 管理者となった方を対象としたコースです。これから組織で Google Workspace のベスト プラクティスを実施し、手法を確立していく方に適しています。これらのコースを受講することで、管理コンソールの基本機能の使い方を習得でき、ユーザーの管理、サービスへのアクセスの制御、セキュリティの設定などを行えるようになります。 一連の学習用教材、段階的な実践演習、理解度チェックを通じて、Google Workspace 管理者として業務を開始するために必要なスキルをすべて身につけることができます。 このコースでは、Google Workspace アカウントの登録と Google Workspace 用 DNS レコードの設定を行います。ユーザーのプロビジョニングと管理方法について学習し、組織のグループおよびカレンダー リソースを作成します。また、Cloud Directory の概要を把握し、組織を複数の組織部門に分割してユーザーおよびサービスの管理を簡素化する方法を学びます。さらに、組織の他のユーザーに管理者権限を委任する方法も学びます。 重要: 受講者がこのトレーニング コースを最大限に活用するには、次の準備をしておく必要があります。 - enom、GoDaddy などの登録事業者を通じて新しいドメインを購入します。注: 試用にあたり、すでにお持ちのドメインを使うこともできます。ただし、このコースでは、既存のドメインと Google Workspace トライアル アカウントを関連付ける詳しい手順については説明しません。こうした関連付けの詳しい手順については、ヘルプセンター記事（https://support.google.com/a/topic/9196）をご覧ください。 - Google Workspace アカウントの設定に必要となるクレジット カード情報を用意しておきます。このコースでは、14 日間の Google Workspace トライアル アカウントを使用します。アカウント登録の際、クレジット カード情報が必要になります。試用期間中は、クレジット カードに対して Google Workspace の料金が請求されることはありません。請求を避けるためには、試用期間が終了する前にサブスクリプションをキャンセルする必要があります。この手続きは非常に重要ですので、忘れないようにしてください。 - https://www.google.com/chrome/ から Chrome ウェブブラウザの最新バージョンをインストールして使用できるようにしておきます。
DeepLearning.AI
AI for Medical Diagnosis
AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine: - In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders. - In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis. - In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. As a learner, you will be set up for success in this program if you are already comfortable with some of the math and coding behind AI algorithms. You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by deeplearning.ai and taught by Andrew Ng. The demand for AI practitioners with the skills and knowledge to tackle the biggest issues in modern medicine is growing exponentially. Join us in this specialization and begin your journey toward building the future of healthcare.
Google
Data Structures in Python
In this course, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. By the end of this course, you will be able to: • Explain how to manipulate dataframes using techniques such as selecting and indexing, boolean masking, grouping and aggregating, and merging and joining • Describe the main features and methods of core pandas data structures such as dataframes • Describe the main features and methods of core NumPy data structures such as arrays and series • Define Python tools such as libraries, packages, modules, and global variables • Describe the main features and methods of built-in Python data structures such as lists, tuples, dictionaries, and sets