The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
28DIGITAL
Quantitative Formal Modeling and Worst-Case Performance Analysis
Welcome to "Quantitative Formal Modeling and Worst-Case Performance Analysis," an intellectually stimulating course designed to hone your abstract thinking skills in the realm of theoretical computer science. This course invites you to dive deep into the world of token production and consumption, a foundational approach to system behaviour. Master the art of mathematically formalizing these concepts through prefix orders and counting functions. Get hands-on with Petri-nets, explore the nuances of timing, and delve into the scheduling intricacies of token systems. You'll even learn to conduct worst-case performance analysis on single-rate dataflow graphs, examining key metrics like throughput, latency, and buffering. Why the focus on small examples rather than industrial-size systems? The aim here is twofold: First, we strive to cultivate your ability to think abstractly and mathematically about modelling and performance—a vital skill for tackling any future challenges in this field. Second, while dataflow techniques are indeed industry-applicable, this course serves as an essential primer that focuses on single-rate dataflow, the cornerstone of more advanced dataflow techniques. And here's a bonus: this course forms part of the esteemed Quantitative Evaluation of Embedded Systems (QEES) curriculum offered under the aegis of the EIT-Digital University and the Dutch 3TU consortium. While the examination for QEES is more advanced, this course perfectly mirrors its initial three-week content, offering you a robust academic experience online. Ready to sharpen your abstract thinking and delve into the fascinating world of formal modelling? Enroll now to secure your spot.
Packt
Building Microservices API in Go
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. If you're eager to advance your programming skills, mastering Go is essential in today's tech environment. This course offers a deep dive into Go programming, focusing on building efficient and scalable microservices using REST-based APIs. - You'll explore security best practices, including authentication, authorization, role-based access control, and JWT token generation. - You'll covers unit testing techniques, such as state-based testing, testing routes and services, and using mocks and stubs. - Additionally, you'll learn about logging and error handling, creating Go modules for better code organization. - You'll modularize your code with the banking-lib module, integrate it into your APIs, and understand Claims domain objects and refresh tokens for secure access. By the end, you'll be proficient in building secure, reliable Go applications and optimizing code organization. Ideal for developers, college students, and IT professionals, this course elevates your Go programming and microservices skills.
Coursera
Track and Update Vendor Performance Data
This beginner-level course is for anyone entering a role in procurement, logistics, or operations who needs to master a fundamental business skill: accurately tracking and updating vendor performance data. In approximately 90 minutes, you will learn the precise, step-by-step process that turns raw data into reliable business intelligence. This is a practical, hands-on course that focuses entirely on the job task. In the first module, you will build a solid foundation, learning the "why, where, and when" of data tracking and mastering how to locate the correct information in a shared system. In the second module, you will put that knowledge into action, following a guided process to accurately enter and verify data in a hands-on lab. You will see how your attention to detail connects to real-world outcomes, from ensuring product safety to upholding a company's ethical standards. You will leave this course with the confidence and skill to be a reliable contributor to your team's data management process from day one.
University of Toronto
Spatial Analysis and Satellite Imagery in a GIS
In this course, you will learn how to analyze map data using different data types and methods to answer geographic questions. First, you will learn how to filter a data set using different types of queries to find just the data you need to answer a particular question. Then, we will discuss simple yet powerful analysis methods that use vector data to find spatial relationships within and between data sets. In this section, you will also learn about how to use ModelBuilder, a simple but powerful tool for building analysis flowcharts that can then also be run as models. You will then learn how to find, understand, and use remotely sensed data such as satellite imagery, as a rich source of GIS data. You will then learn how to analyze raster data. Finally, you will complete your own project where you get to try out the new skills and tools you have learned about in this course. Note: software is not provided for this course.
Advancing Women in Tech
Real-World Cloud PM 2 of 3: Managing, Innovating, Pricing
Sponsored by AMAZON WEB SERVICES (AWS). Learn real-world technical and business skills for product managers or any job family involved in the rapidly expanding cloud computing industry. Ace the AWS Certified Cloud Practitioner Exam. This course is the 2nd in a 3-course Specialization. Complete the first course before attempting this one. Featuring * NANCY WANG, GM of AWS Data Protection Services, AWS; Founder and CEO, Advancing Women in Tech (AWIT) * GORDON YU, Technical Product Manager, AWS; General Counsel and Coursera Director, AWIT
American Psychological Association
t-Tests of Hypotheses About Means
This is primarily aimed at first- and second-year undergraduates interested in psychology, data analysis, and quantitative research methods along with high school students and professionals with similar interests. This course provides a comprehensive understanding of statistical methods for comparing means, focusing on the t-test. Students will learn to conduct and interpret one-sample, paired-samples, and independent-samples t-tests, using raw data and summary statistics. The course also covers calculation and interpretation of effect sizes, confidence intervals, and statistical power. Table of Contents: The t-Statistic The The Varieties of t-Tests and When To Use Them The One-Sample t-Test The Paired-Samples t-Test The Independent-Samples t-Test
Packt
The Complete Guide to Data Preparation for Analysis
This course 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. In this comprehensive course, you'll dive into essential frameworks and techniques for data preparation, exploring everything from data collection to cleaning. You’ll discover how to apply frameworks for mobile, web, and real-time data streaming, as well as cloud-based systems to collect and analyze data efficiently. The course offers in-depth exploration into survey design and data standardization, ensuring that you understand both the theory and practical applications of these concepts. The journey through this course begins with foundational knowledge, advancing through frameworks for collecting and standardizing data. You'll also work on hands-on projects that involve creating survey questions, administering surveys, and applying various cleaning techniques to real-world datasets. As you progress, the course builds on each module to ensure a smooth and comprehensive learning experience. This course is ideal for data professionals, analysts, or anyone involved in data analysis and preparation. A background in data science or information technology would be helpful but is not mandatory. The course is designed to be approachable while still providing deep, advanced insights into data preparation. By the end of the course, you will be able to effectively collect, standardize, clean, and prepare data for analysis using various frameworks and tools, ensuring the highest data quality and integrity.
Packt
Building Modular Monoliths with .NET 8
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. In this course, you will learn how to develop modular monoliths using .NET 8, a modern approach to building scalable, maintainable, and flexible applications. By the end, you'll be proficient in creating modular monoliths that offer the benefits of both traditional monolithic architectures and microservices, avoiding the pitfalls of both. You'll explore key concepts like vertical slice architecture, dependency injection, domain-driven design (DDD), and clean architecture while gaining practical experience in building modular components. The course begins with an overview of modular monoliths and their advantages over traditional monolithic architectures and microservices. You'll also get a deep dive into the limitations of traditional monoliths and the common issues with microservices architecture, such as technology lock-in and distributed monoliths. After building a solid foundational understanding, you will explore modular monoliths, particularly through the lens of real-world examples such as Shopify's architecture and Amazon's transition from microservices back to a monolithic structure. Moving forward, you will dive into creating a complete modular monolith solution, beginning with setting up project structures, establishing folder hierarchies, and organizing dependencies. You'll explore the various layers and modules of the application, ensuring that each module is developed with best practices for scalability and maintainability. Special attention is given to domain modeling using DDD, implementing CQRS, and structuring APIs to achieve separation of concerns while optimizing for modularity. This course is perfect for developers looking to transition from traditional monoliths to modular architectures or those seeking a robust understanding of .NET-based modular monoliths. No prior experience with .NET 8 is required, though a basic understanding of C# and software development principles will be helpful. Whether you're working on large-scale enterprise applications or smaller projects, this course provides the tools and techniques to design and implement a highly maintainable and scalable solution.
Erasmus University Rotterdam
Mind of the Universe: Science in Progress
From William Harvey discovering the circulation of blood to Albert Einstein developing the theory of relativity: almost all scientific research starts from something odd and unexpected that hasn't been explained yet, and, subsequently, the scientist creatively imagining possible explanations for it, formulating hypotheses. However, the problem with formulating hypotheses is the "theory-ladenness of observation": ones expectations and background theories curtail and determine what one observes. The best way to reduce the negative consequences of theory-ladenness of observation as much as possible, is not by adopting the highest methodological standards, but by continuing to think outside the box throughout the problem solving process, by tirelessly, creatively imagining alternative explanations and hypotheses. In this learning experience you will be turned upside down by philosopher Tim de Mey, who will challenge you to think outside of your comfort zone. You will be challenged to reflect critically and creatively on what triggers your research, i.e., what is driving the scientist in you. Tim will show you how openness to and interaction with other disciplines generates new ideas, and how important it is that scientists, besides the possibilities of their own discipline, are also aware of its (and there) limitations. Take this challenge and you will construct the perfect out-of-the-box research question that will tease the Mind of the Universe scientists to explore even better answers in their research. This online learning experience is a spin-off of The Mind of the Universe documentary series created by the Dutch broadcasting company VPRO and professor Robbert Dijkgraaf, Princeton University. A number of universities in the Netherlands have used the open source material of the documentary series as a starting point to create similar experiences.
Illinois Tech
Cloud: Infrastructure as a Service - Master's
Infrastructure as a Service (IaaS) allows users to provision processing, storage, networks, and other fundamental computing resources which then allows them to deploy and run arbitrary software, which can include operating systems and applications. Students will learn how to provision, deploy and manage operating systems, storage, and deployed applications as well as virtual networking components such as switches, routers, and firewalls in a cloud environment accessible remotely through a network. By the end of this course, students will be able to: - Use concepts of cloud computing and cloud native applications to provision. - Deploy and manage operating systems, storage, and deployed applications as well as virtual networking components such as switches, routers, and firewalls in a cloud environment accessible remotely through a network, using standard planning methodologies to meet identified business and/or consumer needs.
University of California San Diego
Teaching Impacts of Technology: Data Collection, Use, and Privacy
In this course you’ll focus on how constant data collection and big data analysis have impacted us, exploring the interplay between using your data and protecting it, as well as thinking about what it could do for you in the future. This will be done through a series of paired teaching sections, exploring a specific “Impact of Computing” in your typical day and the “Technologies and Computing Concepts” that enable that impact, all at a K12-appropriate level. This course is part of a larger Specialization through which you’ll learn impacts of computing concepts you need to know, organized into 5 distinct digital “worlds”, as well as learn pedagogical techniques and evaluate lesson plans and resources to utilize in your classroom. By the end, you’ll be prepared to teach pre-college learners to be both savvy and effective participants in their digital world. In this particular digital world (personal data), you’ll explore the following Impacts & Technology pairs -- Impacts (Show me what I want to see!): Internet Privacy, Custom Ads, Personalization of web pages Technologies and Computing Concepts: Cookies, Web vs Internet, https, Web Servers Impacts (Use my data…. But protect it!): Common Cybersecurity knowledge levels, ISP data collection, Internet design, finding out what is known about you online, software terms and services Technology and Computing Concepts: DNS, Cryptography (ciphers, hashing, encryption, SSL), Deep and Dark Web Impacts (What could my data do for me in the future?): What is Big Data, Machine Learning finds new music, Wearable technologies. Technology and Computing Concepts: AI vs ML, Supervised vs Unsupervised learning, Neural Networks, Recommender systems, Speech recognition In the pedagogy section for this course, in which best practices for teaching computing concepts are explored, you’ll learn how to apply Bloom’s taxonomy to create meaningful CS learning objectives, the importance of retrieval-based learning, to build learning activities with online simulators, and how to use “fun” books to teach computing. In terms of CSTA K-12 computer science standards, we’ll primarily cover learning objectives within the “impacts of computing” concept, while also including some within the “networks and the Internet” concepts and the “data and analysis” concept. Practices we cover include “fostering and inclusive computing culture”, “recognizing and defining computational problems”, and “communicating about computing”.
Pearson
Certified Kubernetes Security Specialist (CKS): Unit 1
This course breaks down the CKS certification process, clarifying exam requirements and helping you create an effective study plan. You’ll set up and manage your own Kubernetes home lab, both locally and in the cloud, to practice real-world scenarios. Key topics include Kubernetes security fundamentals, cloud-native application protection, threat modeling, and an overview of Kubernetes architecture and public key infrastructure. You’ll also analyze real hacking incidents and top OWASP risks to learn how to spot and fix vulnerabilities. Whether you want certification or to strengthen your Kubernetes skills, this course gives you practical knowledge and strategies for today’s cloud-native environments.
Coursera
Scrape and analyze data analyst job requirements with Python
In this project, you’ll help a recruitment agency improve its job vacancy sourcing by using Python’s web-scraping capabilities to extract job postings from multiple sites. This task will require you to write a Python script to extract job posting data from the source site and save it to a comma separated values (CSV) file. Your work will help the agency provide clients with with relevant job openings more quickly, giving them a competitive advantage over other applicants. There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers. ROLE: Data Analyst SKILLS: Python PREREQUISITES: variables, data types, loops, functions, and file input/output in Python web scraping techniques data cleaning, preprocessing, and visualization techniques BeautifulSoup, Git, Jupyter Notebook
University of Michigan
Brilliant, Passionate You
This course is an interdisciplinary look at how we can make each day the best day of our lives by examining the question, “How can you be your most brilliant, passionate self?” You will be joined on this journey by our animated host, Lewis! You will envision your “perfect day” and then slowly deconstruct the elements of that day to better understand key elements such as finding your purpose, defining success, mental and physical health, the importance of community, and navigating risks and challenges. In addition, you will hear stories from a diverse array of individuals, including students, doctors, teachers, professional storytellers, professional athletes, coaches, and others sharing their own journeys, communities, and sources of inspiration. Finally, you will participate in the What’s Your Purpose? Project, utilizing storytelling techniques to share your own purpose and inspire other members of this global learning community to pursue theirs.
Deep Teaching Solutions
Aprendiendo a aprender: Poderosas herramientas mentales con las que podrás dominar temas difíciles (Learning How to Learn)
Este curso te brinda acceso a invaluables técnicas de aprendizaje utilizadas por expertos en arte, música, literatura, matemáticas, ciencia, deportes y muchas otras disciplinas. Aprenderemos cómo el cerebro utiliza dos modos de aprendizaje muy distintos y cómo encapsula (“fragmenta”) la información. También hablaremos sobre ilusiones de aprendizaje, técnicas de memoria, cómo ocuparse de la procrastinación y las mejores prácticas, según lo demuestra la investigación, para ayudarte a dominar los temas más complicados. Con estos enfoques, más allá de tus niveles de destreza en los temas que quieras dominar, puedes cambiar tu pensamiento y tu vida. Si ya eres un experto, este vistazo de la maquinaria cerebral te dará ideas para disparar un nuevo aprendizaje poderoso, con consejos contraintuitivos para presentar exámenes y perspectivas que te ayudarán a aprovechar al máximo el tiempo que dedicas a las tareas y a la resolución de problemas. Si estás teniendo dificultades, descubrirás un cofre del tesoro estructurado con técnicas prácticas que te orientan acerca de lo que debes hacer para mejorar. Si alguna vez deseaste ser mejor en algún ámbito del aprendizaje, este curso te servirá como guía. Este curso también está disponible otros idiomas: Para unirte a la versión en inglés, visita: https://www.coursera.org/learn/learning-how-to-learn Para unirte a la versión en portugués, visita: https://www.coursera.org/learn/aprender Para unirte a la versión en chino, visita: https://www.coursera.org/learn/ruhe-xuexi
Google Cloud
Serverless Data Processing with Dataflow: Operations em Português Brasileiro
Na última parte da série de cursos do Dataflow, vamos abordar os componentes do modelo operacional do Dataflow. Veremos ferramentas e técnicas para solucionar problemas e otimizar o desempenho do pipeline. Depois analisaremos as práticas recomendadas de teste, implantação e confiabilidade para pipelines do Dataflow. Por fim, faremos uma revisão dos modelos, que facilitam o escalonamento dos pipelines do Dataflow para organizações com centenas de usuários. Essas lições garantem que a plataforma de dados seja estável e resiliente a circunstâncias imprevistas.