The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Packt
HTML, CSS, and JavaScript Basics with Simple Projects
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. This course introduces the core web development technologies—HTML, CSS, and JavaScript—through fun, hands-on projects. You’ll begin by setting up your environment using Visual Studio Code. Then, you’ll build real-world mini projects like a Photo Gallery, BMI Calculator, Currency Converter, and Note App to master the fundamentals of structure, styling, and interactivity. Each section combines coding exercises with clear explanations, helping you create visually appealing and functional web pages. As you progress, you’ll explore more creative projects like a Random Quote Generator and Feedback UI to enhance your problem-solving and design skills. This course is ideal for beginners, students, and aspiring web developers. No prior coding experience is required—just curiosity and a passion for learning. By the end, you’ll be able to build interactive websites from scratch and confidently apply HTML, CSS, and JavaScript to create engaging user experiences.
Peking University
遗传学实验
本课程的实验设计贯穿以研究基因功能为目的遗传学思维理念及精髓。通过背景知识的介绍和相关的实验操作，使大家建立这样的理念：研究基因功能时，在分子水平通过敲除或者敲入的策略，使基因突变或者修饰，这些突变依赖载体染色体的传递，将稳定地传给下一代。通过设计精巧的遗传杂交实验，追踪易于识别的染色体标记，就可以定位目的基因、获得纯合突变体，研究表型与基因型间的对应关系，从而理解各种表型的分子机制。整个实验过程涉及生物学不同学科知识和实验设计的融合。 针对遗传学研究的这些关键点，本课程设计了一系列实验，主要以模式动物果蝇为窗口，通过遗传杂交实验，以遗传信息传递的载体染色体为线索，除验证遗传学基本定律外，还引入科研项目的理念和实验环节，以便让大家参与平时在课堂上接触不到的真实科研实践。每次实验包括背景原理、目的介绍、操作要点和相关的视频演示。让学生亲自保管和观察杂交果蝇培养瓶，写生活史观察日记也是本课程的特色之一。 学生，尤其是高年级本科生和进入国内外科研第一线的研究生，均反馈受益非浅。 参考教材为由张文霞主编，高等教育出版社出版的《遗传学实验指导》。此外相应的实验将提供参考文献。 MOOC实验课虽然无法亲自操作，但我们将提供丰富的图片和视频资料，使大家了解其过程。有实验条件的选课人员，可以依照讲解和演示，亲自操作。
Coursera
Naive Bayes 101: Resume Selection with Machine Learning
In this project, we will build a Naïve Bayes Classifier to predict whether a given resume text is flagged or not. Our training data consist of 125 resumes with 33 flagged resumes and 92 non flagged resumes. This project could be practically used to screen resumes in companies.
HRCI
Talent Acquisition
**The Talent Acquisition Course won Coursera's 2024 Learners First Award, which honors the instructor and course team who have received the highest ratings from Coursera learners based on direct feedback.** This course focuses on all aspects of the talent acquisition process. You will learn how to forecast workforce needs, source and recruit talented candidates, and hire and onboard new employees. By the end of this course, you will be able to: ● Create a recruitment strategy ● Perform a job analysis and write a job description ● Explain the talent acquisition life cycle ● Identify core elements of negotiation, job offers, and employment contracts ● Implement best practices for employee onboarding No prior experience in Human Resources is needed to be successful in this course.
Coursera
Testing and Profiling in NetBeans: Fix a Mortgage Calculator
In this 1.5-hour long project based course, you will learn how to use NetBeans 20 to unit test, debug, verify, and profile the performance of a Java application using JUnit and the built-in debugger and profiler of NetBeans. NetBeans is a popular integrated development environment (IDE) in the IT industry. It can be used for Java, PHP, HTML, CSS, JavaScript, and C++ development. We will use Java in the project. However the skills you acquired will be applicable to other programming languages as well. This course is aimed at learners who have basic knowledge of Java and want to learn how to use an IDE for quality assurance life cycles. Required pre-requisites are: core Java, Java package structures, Java data types, string and number manipulations, Java functions.
University of Glasgow
6G Deployment: Testbeds, Antenna Systems & Digital Twins
The final part of this specialization in 6G wireless technologies will enable learners to understand digital twins-enabled wireless communications, master antenna design principles for 6G applications, explore comprehensive testbed implementations and industry use cases, and analyze 6G's ubiquitous connectivity vision. Learners will gain expert insights into how these implementation-focused technologies will enable practical deployment of next-generation wireless systems. Part 3 focuses on real-world implementation and deployment aspects, examining digital twin fundamentals in telecommunications, antenna array design principles, testbed experimentation platforms, and industry applications. The integrated approach covers theoretical antenna physics, practical testbed configurations, and futuristic outlook discussions from industry leaders. Expert perspectives provide insights into building the road to 6G through trials, standardization, and ecosystem collaboration. By completing Part 3, learners will be equipped with specialized knowledge in 6G implementation, testing, and deployment strategies, positioning them to lead practical 6G development initiatives. This final part of the specialization builds upon the foundational concepts from Parts 1 and 2, creating a complete pathway to 6G expertise that encompasses everything from theoretical principles to real-world deployment.
Google Cloud
Transformer Models and BERT Model - Italiano
Questo corso ti introduce all'architettura Transformer e al modello BERT (Bidirectional Encoder Representations from Transformers). Scopri i componenti principali dell'architettura Transformer, come il meccanismo di auto-attenzione, e come viene utilizzata per creare il modello BERT. Imparerai anche le diverse attività per le quali può essere utilizzato il modello BERT, come la classificazione del testo, la risposta alle domande e l'inferenza del linguaggio naturale. Si stima che il completamento di questo corso richieda circa 45 minuti.
Stanford University
Fundamentals of Machine Learning for Healthcare
Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles. This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare. The course will empower those with non-engineering backgrounds in healthcare, health policy, pharmaceutical development, as well as data science with the knowledge to critically evaluate and use these technologies. Co-author: Geoffrey Angus Contributing Editors: Mars Huang Jin Long Shannon Crawford Oge Marques In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.
Google
AI Fundamentals
Ready to move beyond the buzz and see real results with AI? This course covers the fundamentals of working with AI, like understanding its strengths and limitations so you can leverage it effectively at work. You’ll learn how to give AI clear and specific instructions, called prompts, and how to use AI responsibly by maintaining a “human-in-the-loop” approach. By the end of this course, you will: • Adopt a new way of working with AI, moving beyond a simple task completer to a professional collaborator. • Apply prompting techniques to brainstorm new ideas and build a library of reusable prompts for daily tasks. • Practice prompt chaining to solve complex, multi-step problems. • Generate custom images by learning how to effectively communicate your creative vision. • Use responsible judgement to apply AI confidently.
EDUCBA
Linear Regression with R: Build & Optimize
By the end of this course, learners will be able to define core concepts of Linear Regression, construct simple and multiple regression models, apply dummy variable techniques, and evaluate model performance using statistical tests. Participants will also develop the ability to optimize models through backward elimination and validate predictive accuracy on new datasets. This course is designed to provide a step-by-step learning pathway from the fundamentals of regression equations to advanced applications in supervised machine learning with R. Learners will gain practical skills by working on real-world datasets, interpreting regression outputs, and visualizing model performance. Unlike theoretical courses, this program emphasizes hands-on practice, allowing participants to strengthen both conceptual understanding and applied expertise. What makes this course unique is its clear progression from basic linear models to advanced optimization methods, ensuring accessibility for beginners while delivering depth for advanced learners. Whether you are a student, analyst, or professional, this course equips you with the knowledge and confidence to apply regression techniques effectively in data-driven decision-making.
Simplilearn
Javascript Basics with Operators, Loops and Functions
This comprehensive JavaScript course will equip you with essential skills to build dynamic and responsive web applications. You’ll learn the fundamentals, control program flow, solve real-world problems, and manipulate the DOM to create interactive websites. By the end of this course, you will be able to: - Master JavaScript Fundamentals: Understand core concepts, key features, and real-world applications, including the Document Object Model (DOM). - Control Program Flow: Use operators, control statements, loops (for, while, do-while), and switch cases to manage logic efficiently. - Solve Practical Problems: Tackle tasks like prime numbers, Armstrong numbers, and factorials using functions and variables. - Work with Data Structures: Organize and manipulate data effectively using arrays and objects. - Manipulate the DOM: Create interactive web content with getElementById() and getElementByClassName(). - Build Dynamic Websites: Integrate all skills to develop responsive, real-world web applications. Perfect for beginners aiming to master JavaScript and create engaging, interactive web experiences.
University of Florida
The Science of Training Young Athletes
Seventy percent of kids drop out of sports before their high school graduation. Only 15% leave because they feel they are not good enough. Almost 70% leave because they were not having fun, or due to problems with the coach. Injuries cause 30% to give up sports. This course is packed full of practical sports science information that provide youth coaches and parents with the practical pediatric sports science insights to successfully retain young athletes and develop their sport potential while avoiding injury and overtraining. We begin by examining the multidimensional nature of coaching, the relevant sport motor performance abilities, the impact of growth and development on motor skills, the gene versus practice controversy, and briefly overview the body structures strengthened through training. Then we explore the athlete's energy supply, where this energy comes from, and how it matures along with the athlete. Finally, we examine the development of strength, power, anaerobic capacity, coordination and flexibility through the life span. The optional text manual for this course is available at: http://www.learnitez.com/HighPerformanceScience/manuals/
University of California, Irvine
Proyecto Final de Éxito Profesional
El propósito del Proyecto Final de la Programa Especializado de Éxito Profesional es que apliques a una experiencia personal los métodos y las técnicas que has aprendido en la serie de cursos, dándote una manera de comunicar tu valor a empleadores potenciales. Centrarás tus habilidades de comunicación, dirección, negociación, resolución de problemas, redacción empresarial, gestión del tiempo, finanzas, emprendimiento y gestión de proyecto en un único proyecto que demostrará tu preparación profesional.
Google Cloud
Essential Cloud Infrastructure: Core Services em Português Brasileiro
Neste curso intensivo sob demanda, os participantes vão conhecer os serviços abrangentes e flexíveis de infraestrutura e plataforma fornecidos pelo Google Cloud, com foco no Compute Engine. Com o auxílio de videoaulas, demonstrações e laboratórios práticos, os participantes têm a chance de conhecer e implantar elementos da solução, incluindo componentes de infraestrutura, como redes, sistemas e serviços de aplicativos. O curso também aborda a implantação de soluções práticas, como chaves de criptografia fornecidas pelo cliente, gerenciamento de segurança e acesso, cotas e faturamento, além do monitoramento de recursos.
University of Colorado Boulder
Forming, Funding, and Launching a Technology Startup Company
This course starts with a close look at entrepreneurial finance, revenue models, and sources of startup funding. Learners will build a revenue model, create a Financial Plan for a new startup idea, and prepare an investor presentation for raising capital. Business legal structures are reviewed and some of the key legal considerations and pitfalls for startups are examined. Intellectual Property (IP) is presented as a business strategy for creating value and building competitive advantage. The role of ethics in a startup environment is explored in the context of an entrepreneurial mindset. The value of building a learning organization is presented. Startup growth strategies for building technology companies and exit options for technology entrepreneurs are reviewed. Learners will complete a business plan for a new product or service idea. Forming, Funding, and Launching a Startup Company can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.
Coursera
Automate, Optimize, and Monitor ML Models
Machine learning models lose accuracy over time without proper monitoring and optimization. This Short Course was created to help ML and AI professionals build robust, production-ready systems that maintain performance at scale. By completing this course, you'll master critical MLOps skills for detecting model drift, implementing automated retraining workflows, and creating optimized ML pipelines that ensure sustained business value in production environments. By the end of this course, you will be able to: - Evaluate production model performance to detect and mitigate drift - Create an automated, end-to-end machine learning pipeline for model optimization This course is unique because it bridges the gap between model development and production operations, focusing on automation and monitoring strategies that prevent costly model failures. To be successful in this project, you should have experience with machine learning fundamentals and Python programming.