The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Coursera
Typescript in React: Higher Order Components
By the end of this course you will be able to start working with higher order components in Typescript applications. We will start by focusing on the core higher order component concepts reinforced by code examples which start off simple to drill the concepts, and toward the end we gradually increase the complexity and variety of real world examples of higher order component logic utility in Typescript. This course is aimed at developers who are familiar with React and Typescript, understand the basics well, and would like to have some more experience, especially using some of the more advanced and dynamic development patterns in React.
EDUCBA
Build Employee Apps with React: Apply Real-World UI Skills
By the end of this course, learners will be able to design reusable React components, implement interactive user interfaces, manage application state effectively, and build complete employee-focused productivity applications. Learners will gain the ability to apply React concepts to real-world scenarios, including form handling, data rendering, and UI customization. This course takes a hands-on, case-study-driven approach to React development by guiding learners through the creation of practical applications used in employee environments. Instead of isolated examples, learners work on realistic features such as custom modal components, agenda and messaging applications, feedback forms, to-do management tools, and data tables. Each module builds progressively, reinforcing best practices in component design, state management, and user interaction. By completing this course, learners will strengthen their problem-solving skills and gain confidence in building scalable, maintainable React applications. The course is uniquely focused on employee productivity use cases, making it especially valuable for developers preparing for real project work or professional React roles.
University of California San Diego
Internet of Things: How did we get here?
It is hard to imagine life without your Smartphone – you have come to rely on it so much – for your work; to stay in touch with family and friends; to capture and share those special moments; to find your way around in a new neighborhood. Did you ever wonder how and when all this happened? Or how and when GPS sensors came to be in your cell phone? In this course, we will explore the convergence of multiple disciplines leading to todays’ Smartphones. You will learn about the birth and evolution of Telephony Networks, Broadcast Networks (TV and Radio) and Consumer Electronics. We will discuss the impact of Internet, (multimedia) content, smartphones and apps on everyday lives. We will then look at how this emerging platform called the Internet of Things – wherein billions and trillions of devices communicating with each other and “the cloud” – could enable unprecedented, innovative products and services. Take this course if you want to understand what great new advances in mobile-enabled products will be coming our way! Learning Goals: This course provides a core grounding in how science and technology have developed to enable the Internet of Things – in a way appropriate for any learner. For those interested in developing further hands-on expertise in designing and developing for the Internet of Things, this course will provide a context to the discoveries and converging technologies that will springboard the next round of innovations. After completing this course, you will be able to: 1. Compare how the telephone system works (that is, peer-to-peer networks) with how media delivery works (that is, broadcast/multicast networks). 2. Explain the tradeoffs between circuit switched networks (that is, dedicated resources) and packet switched networks (that is, shared resources). 3. Tell interesting stories about key innovations that transformed the communications, entertainment and consumer electronics industries. 4. Explain how email, YouTube, SMS, etc. work. 5. Find resources for those wishing to do more of a “deep-dive” into the above topics.
Edureka
Predictive Modeling with Python
This Predictive Modeling with Python course provides a practical introduction to statistical analysis and machine learning with Python. You will learn essential machine learning concepts, methods, and algorithms with a strong emphasis on applying them to solve real-world business and data problems. By the end of the course, you will: - Understand different data types used in statistical analysis. - Learn techniques to manage inconsistent data effectively. - Perform hypothesis testing using parametric and non-parametric tests. - Develop exploratory data analysis (EDA) models using statistical and machine learning methods. - Enhance machine learning models through evaluation and optimization techniques. This course is designed for individuals with a foundational knowledge of Python programming and basic statistical concepts. This course is ideal for aspiring data analysts, data scientists, business executives, machine learning engineers, and anyone passionate about data-driven decision-making Throughout the program, you will gain hands-on experience in statistical and predictive modeling and apply your skills to real-world scenarios. Enroll in "Predictive Modeling with Python" today and take your expertise to the next level!
Kennesaw State University
Branding for Differential Advantage with Jagdish Sheth
This course suggests how branding creates value for the product through standardization and quality assurance. Branding can also differentiate your product or offering compared to competitors. In marketing, it is the ultimate differential advantage. Branding also creates a value independent of the product or service you’re offering. It is an intangible asset often commanding 5-10 times product revenue. For example, the highest brand value today is Apple, which has replaced Coca Cola as the highest intangible value asset.
Coursera
Lleva tu resume al siguiente nivel con Canva
En este proyecto guiado, el alumno tendrá la oportunidad de aprender a escribir y diseñar sus currículos y cartas de presentación utilizando Canva. Canva es un programa de diseño gráfico online que te permite crear y diseñar todo tipo de documentos, composiciones de diseño gráfico y más. Canva es una excelente opción para aquellos que buscan una plataforma fácil de usar y fácil de usar para crear diseños atractivos para sus currículums. Canva tiene muchos elementos que son gratuitos y te da mucha libertad a la hora de diseñar. Además de esto, Canva dispone de contenido de pago que ofrece otro sinfín de elementos y posibilidades para el diseño pero que no son obligatorios ni totalmente necesarios, por lo que el usuario tiene la libertad de elegir cuánto contenido o elementos quiere tener a su disposición. . Canva es una herramienta sumamente útil para quienes recién comienzan e incluso se convierte en una muy buena herramienta para quienes llevan años diseñando en programas más avanzados. Es una opción rápida que no necesita ser instalada en tu computadora y siempre que tengas conexión a Internet, será una herramienta accesible.
Coursera
TikTok Monetization: Collaborate with Brands
This course opens the door to turning your TikTok passion into profit by exploring the platform's diverse monetization opportunities. You'll learn how to set up and optimize TikTok Shop for product sales, leverage livestream shopping features, and position yourself for lucrative brand collaborations and sponsored content deals. You'll also discover how the TikTok Creator Fund works and develop a personalized monetization strategy that aligns with your content style and audience. By the end of this course, you'll identify revenue streams to pursue with a clear roadmap for maximizing your earnings on TikTok.
Oracle
Oracle Cloud Infrastructure Foundations
Welcome to the course OCI Foundations Course. This course is a starting point to prepare you for the Oracle Cloud Infrastructure Foundations Associate Certification. Begin with an introduction of the OCI platform, and then dive into the core primitives, compute, storage, networking, identity, databases, security, and more.
Google Cloud
Einführung in Data Engineering in Google Cloud
In diesem Kurs lernen Sie Data Engineering on Google Cloud sowie die Rollen und Verantwortlichkeiten von Data Engineers kennen und sehen, wie diese mit den Angeboten von Google Cloud zusammenhängen. Außerdem erfahren Sie, wie Sie Herausforderungen im Bereich Data Engineering meistern können.
Instituto Tecnológico de Aeronáutica
Controle Usando a Resposta em Frequência
Neste curso você aprenderá a obter a resposta em frequência de um sistema Linear e Invariante no Tempo (LIT) e a usá-la para projetar controladores que atinjam requisitos de reposta transitória e em regime estacionário. Você aprenderá a obter o diagrama de Bode a partir de dados de amplitude e fase de entradas e saídas senoidais. Também será capaz de esboçar o diagrama de Bode de um sistema dada a sua função de transferência. Outrossim, será capaz de representar a resposta em frequência na carta de Nichols-Black. A fim de se determinar a estabilidade do sistema, você aprenderá a aplicar o critério de Nyquist, que faz uso da resposta em frequência em malha aberta e permite determinar se um sistema será estável em malha fechada. Ao fim do curso, você será capaz de projetar controladores com dinâmica, isto é, com polos e zeros, portanto mais complexos do que um simples ganho de realimentação. Essa flexibilidade permitirá que você projete controladores para satisfazer simultaneamente requisitos de sobressinal e tempo de resposta que seriam impossíveis de atender com um simples ganho. Também poderá com isso alterar as características da resposta em regime estacionário, aumentando as constantes de erro sem alterar (muito) a resposta transitória. Por fim, você aprenderá a projetar controladores do tipo PD, PI e PID, que estão entre os mais disseminados em aplicações de engenharia de controle.
Coursera
Real-time analytics with Spark: User Activity Monitoring
In this hands-on, 1-hour project-based course, you will master real-time data processing using Apache Spark Structured Streaming. This course is designed for data engineers and developers who want to gain practical experience in building streaming data pipelines. You will begin by setting up the Spark environment and learn how to configure micro-batches and fault tolerance mechanisms through checkpointing. Next, you’ll dive into transforming streaming data by applying filters, maps, and aggregations to extract meaningful insights. You'll also handle out-of-order data with watermarks, ensuring the accuracy of your real-time analytics. The course will introduce you to querying streaming data using SQL, allowing you to perform transformations and aggregations on live data. Finally, you will learn to deploy your streaming pipeline to production by writing results to an external sink like Parquet files. This is an intermediate level project and in order to succeed in this course it is recommended to have basic understanding of Apache Spark and API PySpark, proficiency in programming and big data as well and some basic knowledge on writing SQL queries. This is the perfect opportunity for anyone looking to dive into real-time data processing and Spark Structured Streaming!
Coursera
Financial Statements for Liquidity Insights
Discover how to read between the lines of financial statements and uncover what liquidity really says about a company’s financial health. In this course, you’ll connect the balance sheet, income statement, and cash flow statement to understand how liquidity ratios reveal short-term stability and cash agility. Through real-world case studies, interactive labs, and data-driven exercises, you’ll calculate and interpret key ratios, benchmark performance, and communicate findings with confidence. Coach-guided reflections help you turn numbers into narrative — the skill that defines modern financial analysts. By the end, you’ll know not just how to measure liquidity, but how to explain what it means for business decisions.
Coursera
Crie sua primeira campanha com Facebook Ads Manager
Crie uma campanha, com estatísticas e relatórios profissionais sobre o comportamento do público-alvo. Gerencie o Facebook Ads Manager com diferentes contas de anúncios, organizando e dividindo os pagamentos por país, marca ou cliente, acessando uma página ou conta de cliente, ou ainda, compartilhando acesso à sua equipe. Este projeto é ideal para qualquer pessoa interessada no mundo do marketing digital ou empresários que queiram dar um primeiro passo nos conteúdos pagos ou SEM (Search Engine Marketing) e que queiram fortalecer o trabalho de posicionamento orgânico.
Google Cloud
Introduction to Image Generation - 繁體中文
本課程將介紹擴散模型，這是一種機器學習模型，近期在圖像生成領域展現亮眼潛力。概念源自物理學，尤其深受熱力學影響。過去幾年來，在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中，擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論，並說明如何在 Vertex AI 上訓練和部署這些模型。
Johns Hopkins University
Introduction to Reproducibility in Cancer Informatics
The course is intended for students in the biomedical sciences and researchers who use informatics tools in their research and have not had training in reproducibility tools and methods. This course is written for individuals who: - Have some familiarity with R or Python - have written some scripts. - Have not had formal training in computational methods. - Have limited or no familiar with GitHub, Docker, or package management tools. Motivation Data analyses are generally not reproducible without direct contact with the original researchers and a substantial amount of time and effort (BeaulieuJones et al, 2017). Reproducibility in cancer informatics (as with other fields) is still not monitored or incentivized despite that it is fundamental to the scientific method. Despite the lack of incentive, many researchers strive for reproducibility in their own work but often lack the skills or training to do so effectively. Equipping researchers with the skills to create reproducible data analyses increases the efficiency of everyone involved. Reproducible analyses are more likely to be understood, applied, and replicated by others. This helps expedite the scientific process by helping researchers avoid false positive dead ends. Open source clarity in reproducible methods also saves researchers' time so they don't have to reinvent the proverbial wheel for methods that everyone in the field is already performing. Curriculum This course introduces the concepts of reproducibility and replicability in the context of cancer informatics. It uses hands-on exercises to demonstrate in practical terms how to increase the reproducibility of data analyses. The course also introduces tools relevant to reproducibility including analysis notebooks, package managers, git and GitHub. The course includes hands-on exercises for how to apply reproducible code concepts to their code. Individuals who take this course are encouraged to complete these activities as they follow along with the course material to help increase the reproducibility of their analyses. **Goal of this course:** Equip learners with reproducibility skills they can apply to their existing analyses scripts and projects. This course opts for an "ease into it" approach. We attempt to give learners doable, incremental steps to increase the reproducibility of their analyses. **What is not the goal** This course is meant to introduce learners to the reproducibility tools, but _it does not necessarily represent the absolute end-all, be-all best practices for the use of these tools_. In other words, this course gives a starting point with these tools, but not an ending point. The advanced version of this course is the next step toward incrementally "better practices". How to use the course This course is designed with busy professional learners in mind -- who may have to pick up and put down the course when their schedule allows. Each exercise has the option for you to continue along with the example files as you've been editing them in each chapter, OR you can download fresh chapter files that have been edited in accordance with the relative part of the course. This way, if you decide to skip a chapter or find that your own files you've been working on no longer make sense, you have a fresh starting point at each exercise.
SoFi
Managing Debt
This course is aimed at anyone who has debt, is thinking of taking on debt, or wants to better understand debt as part of your overall financial picture. It covers a variety of debt types, as well as debt payment options. The course will help you assess your current debt situation and understand the paths to paying off your debt. This includes categories such as mortgages, credit card debt, and student loans. Learn how to differentiate between good and bad debt, as well as how to think about debt as you work towards your financial goals. This course is geared towards learners in the United States of America.