The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
EDUCBA
Analyze and Build a Real-Time Chat App with Node.js
By the end of this course, learners will be able to analyze the architecture of a real-time chat application, implement server-side logic using Node.js, construct and style a client-side interface with HTML and CSS, manage user input and validation, and apply foundational networking and socket programming concepts to enable real-time communication. This course provides a practical, case-study-driven approach to building a chat application from the ground up. Learners progress step by step through creating the server, designing the client interface, handling usernames, executing the application, and implementing individual messaging features. Core networking principles are introduced in context, allowing learners to clearly understand how client–server communication works in real-time systems. By completing this course, learners gain hands-on experience with Node.js and socket-based communication, strengthening their ability to design interactive, event-driven web applications. What makes this course unique is its focused, end-to-end implementation of a real-world chat use case, bridging conceptual understanding with practical development. This makes the course ideal for beginners and early-career developers seeking applied experience in real-time web application development.
Johns Hopkins University
Neuroscience Methods
The course "Neuroscience Methods" provides hands-on experience with cutting-edge neuroscience methods, equipping you to explore how the brain supports perception, attention, memory, and emotion. You'll gain proficiency in using tools such as neuroimaging, biometric systems, psycho-physiological sensors, and eye trackers to collect and analyze complex datasets. Learn to interpret data through advanced neural imaging and physiological measurement techniques, and critically assess the strengths and limitations of different methods. With a unique combination of theory and practice, this course empowers you to design robust research studies and make informed decisions about measurement tools. By mastering techniques like functional near-infrared spectroscopy (fNIRS) and eye-tracking analysis, you'll uncover valuable insights into cognitive and emotional processes. Whether you're a postgraduate student or researcher, this course will deepen your understanding of neuroscience tools and their applications, preparing you for innovative work in psychological and health-related fields.
Google Cloud
Attention Mechanism - בעברית
בקורס נלמד על מנגנון תשומת הלב, שיטה טובה מאוד שמאפשרת לרשתות נוירונים להתמקד בחלקים ספציפיים ברצף הקלט. נלמד איך עובד העיקרון של תשומת הלב, ואיך אפשר להשתמש בו כדי לשפר את הביצועים במגוון משימות של למידת מכונה, כולל תרגום אוטומטי, סיכום טקסט ומענה לשאלות.
University of Colorado Boulder
Description Design for Interactive Learning Resources
This course gives you easy access to an innovative description design framework used and created by experts in description design who design descriptions for highly interactive learning resources. Interactive learning resources are common, fun, and effective tools that engage learners in the classroom and in remote learning environments. Many of these interactives rely on the visual display. This limits non-visual experiences, and makes many interactive learning resources inaccessible to learners with significant visual impairments or print- and graphics-related disabilities. Descriptions are verbalized text for supporting non-visual access. This course will show you how to create descriptions, the verbalized text, needed to make interactive learning resources (interactives) accessible to learners who are blind or have a visual impairment (learners with BVI). The course weaves together concepts from inclusive design, web accessibility, and general best practices for description design for non-visual access. The main focus of the course is learning about and using the Description Design Framework created by design researchers at PhET Interactive Simulations. Through a series of design tasks, each preempted with examples and demonstrations, the course walks you through how to design descriptions for an interactive of your choosing. While prior experience in web accessibility, interaction design, and description is useful, it is not required for this course. We share many examples from our work, and include tips and design patterns that we have created and actively use to describe our highly interactive science and math simulations. If you have an interest in creating descriptions for interactive learning resources, join us in this course. The Description Design Framework helps us take a methodical approach to the challenging task of designing descriptions for interactives, and we want to share what we know so others can design engaging descriptions that support non-visual access to interactive learning resources.
Skillshare
Navigate Your Dream Studio Job: Thrive in 3D Animation
Ease the transition from student to industry professional by learning how to navigate an in-studio 3D animation role. Madison Erwin started her career as a 3D animator by teaching herself the ins and outs of 3D software like Blender and the workings of the animation industry. Just three years later, she’s gone on to work on projects like Spider-Man: Across the Spider-Verse, I Am Groot, and Doctor Strange in the Multiverse of Madness. Now Madison wants to share everything she learned and did to skyrocket her 3D career to the next level. In this class, Madison will reveal how to start a 3D animation career and navigate your dream job without unnecessary stress or burnout. By learning how to vet contracts, navigate studio hierarchy, and properly handle feedback, you’ll move from a 3D animation student to an industry professional with ease. With Madison by your side, you’ll: * Craft a personalized career goal * Discover the ins and outs of contracts and studio hierarchy * Learn how to handle, implement, and ask for feedback * Build habits to maintain your energy and avoid burnout Plus, Madison will help you create a five-year plan and burnout prevention plan based on her own experience working in the 3D animation industry. Whether you’re a self-taught animator and are curious about what working at a studio would be like or you’re early on in your animation career and looking to sustain success, you’ll leave this class with the tools you need to build a solid career plan and deal with any bumps in the road as you go. You do not need professional experience as a 3D animator to take this class. You’ll need a journal and pen or your preferred note-taking system to follow along with these lessons. Instructor bio: Madison Erwin is a self-taught 3D animator based in LA. Known for her acting and animation skills, she successfully freelanced for a year before taking a role in-house at Sony. Her work has been featured in blockbuster films like Spider-Man: Across the Spider-Verse, Doctor Strange, the Disney Plus Series I Am Groot, and hit game Kena: Bridge of Spirits.
Emory University
Health in Complex Humanitarian Emergencies
The Center for Humanitarian Emergencies is a partnership between CDC's Emergency Response and Recovery Branch and the Rollins School of Public Health that drives global collaboration, research and evidence based training to improve the lives and well-being of populations impacted by humanitarian emergencies. - Center for Humanitarian Emergencies: http://www.che.emory.edu/ - CDC's Emergency Response and Recovery Branch: http://www.cdc.gov/globalhealth/healthprotection/errb/index.html This course covers the technical and management principles that are the basis of planning, implementing, and evaluating health programs for acutely displaced populations in developing countries. The emphasis is on refugees in camp situations. The course includes modules on assessment, nutrition, epidemiology of major health problems, surveillance, and program management in the context of an international relief operation. Course Objectives Upon completion of this course, learners will be able to: 1. Describe a complex humanitarian crisis in terms of magnitude, person, time and place. 2. Calculate basic epidemiology measures. 3. Evaluate the strengths and limitations of epidemiological data within the context of CHE. 4. Develop public health programs and strategies responsive to the diverse cultural values and traditions of the community being served. 5. Identify internal and external problems that may affect the delivery of essential public health services in a CHE. 6. Identify the different technical areas in a public health response in CHEs.
EDUCBA
Apply Microsoft Excel Basics for Data Management
Learners will be able to identify the Excel interface, enter and manage data, perform basic calculations, apply formatting, and organize information using essential Excel tools. They will also learn to control formulas, analyze data visually, and navigate large worksheets efficiently. This course provides a structured, beginner-friendly introduction to Microsoft Excel, designed for learners with little or no prior spreadsheet experience. Through short, focused lessons, learners gain hands-on skills in opening workbooks, navigating the Ribbon, entering data accurately, and performing calculations with confidence. As the course progresses, learners develop practical abilities in formatting data, using tables, applying conditional formatting, and organizing information with sorting, filtering, and freeze panes. What makes this course unique is its step-by-step progression aligned with real workplace tasks, ensuring learners build skills logically without being overwhelmed. Each lesson is tightly aligned with practical outcomes, making the course ideal as a prerequisite for advanced Excel training. By completing this course, learners will improve productivity, reduce errors, and gain a solid foundation for data handling and analysis in professional and academic environments.
Fundação Instituto de Administração
Liderança Equilibrada e Cultura de Inclusão
Nossas boas-vindas ao Curso Liderança Equilibrada e Cultura de Inclusão. Neste curso, você aprenderá que, em qualquer segmento da economia, temos poucas ou muitas mulheres na base, dependendo de qual é o setor, mas sempre temos poucas ou raras mulheres no topo. As mulheres costumam estar relativamente bem representadas no mercado de trabalho, mas podem ser até nulas nos conselhos de administração das empresas, por exemplo. O objetivo deste curso é descrever e discutir como a liderança equilibrada de gênero pode ser uma forma eficiente de gestão no mundo corporativo, por meio de dados e casos reais, assim como ilustrar a cultura de inclusão nas organizações contemporâneas. Ao final deste curso, você será capaz de articular ideias e soluções sobre a equidade de gênero aplicada às organizações, por meio de lideranças mais balanceadas e ambientes que promovem a diversidade. Este curso é composto por quatro módulos, disponibilizados em semanas de aprendizagem. Cada módulo é composto por vídeos, leituras e testes de verificação de aprendizagem. Ao final de cada módulo, temos uma avaliação de verificação dos conhecimentos. Estamos muito felizes com sua presença neste curso e esperamos que você tire o máximo de proveito dos conceitos aqui apresentados. Bons estudos!
Edureka
Fine-Tuning & Optimizing Large Language Models
This course provides a comprehensive, hands-on journey into model adaptation, fine-tuning, and context engineering for large language models (LLMs). It focuses on how pretrained models can be efficiently customized, optimized, and deployed to solve real-world NLP problems across diverse domains. Through structured lessons, demonstrations, and practice assignments, you will learn how to apply transfer learning, parameter-efficient fine-tuning techniques, context engineering strategies, and optimization methods to build scalable and production-ready LLM systems. The course emphasizes both theoretical foundations and practical workflows using modern tooling such as Hugging Face, Trainer APIs, and model monitoring platforms. By the end of this course, you will be able to: - Explain the principles of transfer learning, model adaptation, and parameter-efficient fine-tuning for large language models - Fine-tune pretrained models using techniques such as LoRA and adapters for domain-specific and task-based applications - Design effective context engineering strategies, including context optimization, compression, and scalable context patterns - Evaluate fine-tuned models using task-appropriate metrics and perform error analysis - Optimize, deploy, monitor, and maintain fine-tuned models for efficient and cost-effective production use This course is ideal for machine learning engineers, AI practitioners, NLP developers, and data scientists who want to move beyond prompt-only interactions and gain practical expertise in adapting and deploying LLMs in real-world systems. A working knowledge of Python, machine learning fundamentals, and basic NLP concepts is recommended to get the most out of this course. Join us to master the end-to-end lifecycle of fine-tuning, optimizing, and operationalizing large language models—from pretrained foundations to scalable, production-ready AI solutions.
Unilever
Using Data Analytics in Supply Chain
In the Using Data Analytics in Supply Chain course, you’ll explore the importance of data governance, and learn the fundamental concepts surrounding data. You’ll also learn the tools and processes employed in supply chain analytics, enabling you to gather, analyze, synthesize, validate, and interpret data-driven insights. This ensures that products are efficiently delivered to their destination in a timely and cost-effective manner. By the end of this course, you’ll be able to: Explain the importance of data governance and adhere to data governance policies. Define data analysis objectives, formulate questions, pinpoint data sources, and implement effective data gathering techniques. Conduct data analysis by applying calculations, summarizations, averages, and classification of information to answer the identified data analysis objectives and questions. Identify how to use SQL, Python, or spreadsheets to clean, manage, consolidate, analyze, and visualize data. Differentiate between various scenarios and construct simulations to evaluate outcomes. Use data visualization to present insights effectively to decision-makers.
Google Cloud
Smart Analytics, Machine Learning, and AI on GCP - Italiano
L'integrazione del machine learning nelle pipeline di dati aumenta la capacità di estrarre insight dai dati. Questo corso illustra i modi in cui il machine learning può essere incluso nelle pipeline di dati su Google Cloud. Per una personalizzazione minima o nulla, il corso tratta di AutoML. Per funzionalità di machine learning più personalizzate, il corso introduce Notebooks e BigQuery Machine Learning (BigQuery ML). Inoltre, il corso spiega come mettere in produzione soluzioni di machine learning utilizzando Vertex AI.
Google
AI for Content Creation
Ready to bring your creative ideas to life? In this course, you’ll learn to use AI as your creative partner to generate, refine, and critique assets, helping you move from a rough concept to a polished deliverable in minutes. You’ll learn to generate high-quality images and videos directly in Gemini, then use Gemini in Google Slides to turn basic decks into professional presentations. Beyond that, you’ll learn to use AI as a "creative director" to establish design guidelines and ensure your work is both consistent and impactful. By the end of this course, you will create: • Custom marketing assets: Move from promotional concept to reality by using image and video generation models. • A slide deck from any document: Use Gemini Canvas to instantly turn dense reports or notes into a structured presentation outline, tailored for any audience. • An engaging presentation: Use Gemini in Google Slides to to translate your vision into professional designs and formatting, creating a polished deck in minutes. • A creative review: Act as the lead designer by using AI to establish brand guidelines and generate actionable feedback to refine your work.
Coursera
Generative AI for Data Visualization and Data Storytelling
In today’s data-driven world, harnessing the power of Generative AI to create impactful data visualizations is essential for effective communication and decision-making. This course focuses on utilizing cutting-edge AI tools to transform raw data into dynamic, insightful visual artifacts, enhancing your ability to convey complex information clearly and compellingly. Designed for data analysts, business intelligence professionals, and anyone involved in data storytelling, this course provides practical knowledge and skills to optimize your data visualization processes using AI. You'll explore current and emerging trends in AI-powered visualization platforms, ensuring you stay ahead in the ever-evolving data landscape. During this course, you'll focus on the following learning objectives: -Identify how AI tools transform traditional data visualization practices to produce dynamic, insightful presentations. -Analyze data visualization techniques with LLM-Chat interfaces to enhance understanding and communication of complex information. -Apply generative AI techniques for data storytelling, utilizing visualization methods to create compelling narratives. By completing this course, you'll be equipped to: -Understand and utilize cutting-edge Generative AI tools to create data visualization artifacts. -Gain practical knowledge on optimizing data visualization processes using AI. -Explore current and emerging trends in data visualization through AI-powered visualization platforms. This course is unique because it allows you to convert raw data into intuitive visualizations through various real-world industry examples. Generative AI empowers users to effectively communicate insights and make informed data-driven decisions. Whether you’re new to data visualization or looking to simplify complex information, this course equips you to uncover patterns, trends, and relationships using Generative AI tools. To succeed in this course, you should have a basic understanding of data analysis and charts, along with a willingness to explore innovative AI-driven solutions for data visualization.
EDUCBA
Build an Android Calculator App Using Kotlin
Learners will develop, implement, and evaluate a fully functional Android calculator application using Kotlin and Android Studio. By the end of this course, learners will be able to configure Android project structures, modify Activities, design interactive user interfaces, integrate Gradle dependencies, and implement core calculation logic to produce a working mobile application. This hands-on, project-based course guides learners step by step through the complete Android app development workflow. Starting with understanding the project setup and Activity lifecycle, learners progressively build confidence by creating UI components such as buttons, handling user interactions, and refining application logic in the MainActivity. The course concludes with validating the final output, ensuring the calculator functions correctly in a real Android environment. What makes this course unique is its end-to-end project focus. Rather than isolated concepts, learners work on a single practical project that mirrors real-world Android development practices. This approach helps learners translate theory into application-ready skills. Whether learners are new to Android or strengthening their Kotlin expertise, this course equips them with practical experience essential for building interactive Android applications and advancing mobile development skills.
Alberta Machine Intelligence Institute
Introduction to Applied Machine Learning
This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute.
Amazon Web Services
Developing Generative AI Solutions
In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes the following: - Defining a business use case - Selecting a foundation model (FM) - Improving the performance of an FM - Evaluating the performance of an FM - Deployment and its impact on business objectives This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.