The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
National Taiwan University
紅樓夢(The Red Chamber Dream)
這門課是對中國小說經典《紅樓夢》的分析與詮釋，著重於認識讀者本身與經典間的關係，並從作者的時代背景與社會階層著手，重新剖析這部人所共愛、人各有所擁戴的經典之作。
LearnQuest
Strategic Foundations of Sales Negotiation
Immerse yourself in the essential foundations of sales negotiation—combining classic frameworks, modern psychological insights, digital fluency, and multi-regional tactics. This course equips you with the tools to analyze, prepare, and launch successful negotiations across virtual and in-person environments. Develop your ability to research and plan negotiation strategies, build stakeholder buy-in, and communicate complex value propositions with clarity. Whether working in India, the USA, or engaging Spanish-speaking clients, you’ll master strategies proven to deliver win-win results in today’s business climate. Learners leave ready to build rapport, overcome barriers, and steer negotiations toward positive, lasting outcomes.
Google Cloud
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська
Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.
Google Cloud
Sorumlu Yapay Zeka: Google Cloud ile Yapay Zeka İlkelerinin Uygulanması
Kurumsal yapay zeka ve makine öğreniminin kullanımı artmaya devam ettikçe, bunu sorumlu bir şekilde oluşturmanın önemi de artıyor. Sorumlu yapay zeka hakkında konuşmanın, onu uygulamaya koymaktan çok daha kolay olabilmesi burada bir zorluk oluşturmaktadır. Kuruluşunuzda sorumlu yapay zekayı nasıl işlevsel hale getireceğinizi öğrenmekle ilgileniyorsanız, bu kurs tam size göre. Bu kurs, Google Cloud'un sorumlu yapay zeka yaklaşımını nasıl uyguladığını derinlemesine inceleyerek, kendi sorumlu yapay zeka stratejinizi oluşturmanız için size kapsamlı bir çerçeve sunuyor.
University of Washington
Machine Learning: Regression
Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python.
Emory University
Generative AI in Marketing
Discover the transformative potential of Generative AI in the marketing landscape. This course offers an introduction to generative AI and explores its unique capabilities in the context of marketing. Learn to create compelling visual content and enhance customer engagement through advanced AI tools. Dive into the intricacies of training generative AI models and understand the pivotal role of human input in optimizing AI-driven strategies. Learners will explore the limitations of generative AI tools, such as chatbots, and master the art of prompting and iterating with these systems. The course also covers the practical application of generative AI in customer acquisition and engagement, providing insights into evaluating its effectiveness. This course also covers discussion of the legal debates surrounding generative AI, the concept of fair use, and potential brand concerns. By the end of this course, you will be equipped with the knowledge and skills to harness generative AI responsibly and effectively for marketing success.
University of Leeds
Working with Version Control
Version control is a crucial tool for managing code. Explore the basics of version control and learn how to use it in software development projects. In this course, you will explore Git, a popular version control tool which you will learn to use to create repositories, make commits, and ensure your code is organised and up-to-date. You will also practice Markdown, a widely-used markup language, used to create professional and concise documentation for your software projects. You will explore Markdown syntax essentials, enabling you to create headings, lists, links, and images. By the end, you'll be equipped to produce polished documentation that complements your code repositories. Gaining confidence in version control and Markdown, you'll adhere to best practices in organising, updating, and maintaining your code. This course is one of many, offered by Click Start, a UK training programme designed to help young people develop digital skills. Click Start offers a limited number of scholarships giving free access to young people in the UK. Check the FAQs to see more detail and follow the link to check if you are eligible for free access today.
Google Cloud
Serverless Data Processing with Dataflow: Operations
In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
Imperial College London
TensorFlow 2 시작하기
TensorFlow 2 시작하기 과정에 오신 것을 환영합니다! 이 과정에서는 순차 API를 사용한 모델 구축, 훈련, 평가 및 예측, 모델 검증, 정규화, 콜백 구현, 모델 저장 및 로딩 등 Tensorflow를 사용하여 딥 러닝 모델을 개발하기 위한 완벽한 엔드-투-엔드 워크플로우를 배우게 됩니다. 배운 개념을 실용적인 실습형 코딩 자습서에서 바로 연습할 것이며 이는 대학원 조교에게 안내를 받게 될 것입니다. 또한 기술을 통합할 수 있는 일련의 자동 채점 프로그래밍 과제가 있습니다.\n\n과정이 끝나면 이미지 분류기 딥 러닝 모델을 처음부터 개발하는 Capstone 프로젝트에 많은 개념을 통합할 것입니다. Tensorflow는 오픈 소스 머신 라이브러리이며 딥 러닝에 가장 널리 사용되는 프레임워크 중 하나입니다. Tensorflow 2의 출시는 초심자에서 고급 수준에 이르기까지 모든 사용자의 사용 편의성에 중점을 둔 제품 개발의 단계적 변화를 나타냅니다. 이 과정은 Tensorflow 1.x에 대한 경험이 있는 사용자뿐만 아니라 경험이 없는 사용자 모두를 대상으로 합니다. 이 과정에서 성공하기 위해서는 파이썬 프로그래밍 언어(이 과정에서는 파이썬 3 사용), 일반적인 머신 러닝 개념(예: 과적합/과소적합, 지도 학습 작업, 검증, 정규화 및 모델 선택), 전형적인 모델 아키텍처(MLP/피드포워드 및 컨볼루션 신경망), 활성화 함수, 출력 레이어 및 최적화를 포함한 딥 러닝 분야의 실무 지식을 갖추고 있어야 합니다.
Johns Hopkins University
Foundational Mathematics for AI
This course offers a comprehensive introduction to the mathematical principles that form the foundation of artificial intelligence and machine learning. Designed for learners with a variety of academic backgrounds, the course bridges essential mathematical concepts with real-world AI applications, empowering students to understand and implement mathematical techniques critical for AI development. By the end of this course, learners will be able to apply functions, matrices, and vectors to represent and analyze data relationships. Students will be able to use descriptive statistics and visualization techniques to explore and summarize datasets, solve systems of linear equations and model complex relationships using linear regression of single and multiple variables, and understand and implement foundational principles of probability, including Bayes' Theorem. The course builds to advanced mathematical techniques in Calculus, and develops derivatives and integrals to analyze rates of change and distributions, essential for optimization and modeling in AI. Concepts from Linear Algebra are used to explore advanced concepts like eigenvectors, determinants, and linear transformations for dimensionality reduction and classification algorithms. This course is specifically tailored for aspiring AI practitioners. Unlike traditional math courses, this curriculum focuses on mathematical techniques directly applicable to artificial intelligence and machine learning, bridging theory with practice. Through interactive modules, real-world datasets, and tools like Python and Excel, you’ll not only understand the concepts but also apply them to solve practical problems. With clearly defined modules such as Descriptive Statistics, Linear Algebra, Probability, and Optimization, this course allows you to build knowledge progressively while connecting each concept to AI use cases. Each topic is introduced with AI-related examples, like using linear regression to model salaries or applying optimization techniques in clustering algorithms, with then a focus on applications of the theory. This course equips you with the mathematical fluency necessary for more advanced AI courses and research, such as deep learning or natural language processing. Whether you’re an engineer, data scientist, or simply interested in breaking into AI, this course provides the mathematical foundation you need to understand and contribute to the rapidly evolving field of artificial intelligence.
Coursera
Collect and Share Employee Feedback with Officevibe
Officevibe is an online feedback tracker that helps human resources and managers alike keep a finger on the pulse of their organization and teams. Whether it’s conducting one-on-one meetings, creating team surveys and reports to better understand your team, or preparing employee reviews – Officevibe can do it all. Officevibe is a simple platform which can help you perform all of your management duties while developing trust, fostering collaboration, and improving overall team performance. The goal of Officevibe is to focus on the human side of the job and create a more efficient and effective team through personal connections. This project will explore the many free features of Officevibe and get you well on your way to becoming a more effective leader. Officevibe’s easy to use features allow you to streamline the feedback process and maximize your conversations with your employees. With Officevibe, feedback goes both ways which allows you to eliminate blind spots and better develop your employees and team. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
University of Pennsylvania
Wonders of Ancient Egypt
Colossal pyramids, imposing temples, golden treasures, enigmatic hieroglyphs, powerful pharaohs, strange gods, and mysterious mummies are features of Ancient Egyptian culture that have fascinated people over the millennia. The Bible refers to its gods, rulers, and pyramids. Neighboring cultures in the ancient Near East and Mediterranean wrote about its god-like kings and its seemingly endless supply of gold. The Greeks and Romans describe aspects of Egypt's culture and history. As the 19th century began, the Napoleonic campaign in Egypt highlighted the wonders of this ancient land, and public interest soared. Not long after, Champollion deciphered Egypt's hieroglyphs and paved the way for other scholars to reveal that Egyptian texts dealt with medicine, dentistry, veterinary practices, mathematics, literature, and accounting, and many other topics. Then, early in the 20th century, Howard Carter discovered the tomb of Tutankhamun and its fabulous contents. Exhibitions of this treasure a few decades later resulted in the world's first blockbuster, and its revival in the 21st century has kept interest alive. Join Dr. David Silverman, Professor of Egyptology at Penn, Curator in Charge of the Egyptian Section of the Penn Museum, and curator of the Tutankhamun exhibitions on a guided tour of the mysteries and wonders of this ancient land. He has developed this online course and set it in the galleries of the world famous Penn Museum. He uses many original Egyptian artifacts to illustrate his lectures as he guides students as they make their own discovery of this fascinating culture. This course focused on five key areas in the study of Ancient Egypt: 1) Principles of Egyptian Art, 2) The Basics of the Language of Ancient Egypt: Hieroglyphs, 3) Egyptian Magic, 4) Akhenaten, Tutankhamun, and the Religion of the Aten, and 5) The Burial of Tutankhamun and the Search for his Tomb. This course is intended to accompany, and ideally to follow, Introduction to Ancient Egypt (also available on Coursera).
DeepLearning.AI
Python for Data Analytics
This comprehensive course guides students through the complete data analytics workflow using Python, combining programming fundamentals with advanced statistical analysis. The curriculum is structured across five interconnected modules that build upon each other, using real-world datasets to provide practical, hands-on experience. Starting with programming fundamentals, you'll learn essential Python concepts while working with real datasets like public library revenue and restaurant safety inspections. The course introduces the Jupyter Notebook environment and transitions students from spreadsheet-based analysis to powerful programmatic approaches. Students master core programming concepts including variables, functions, and control flow structures. This course helps you bridge the gap between theoretical knowledge and practical application, enabling you to become proficient in using Python for comprehensive data analysis, from basic data manipulation to advanced statistical modeling and forecasting.
IBM
Machine Learning with Python
Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP. Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills. Enroll now to start building machine learning models with confidence using Python.
Corporate Finance Institute
Advanced Tableau - LOD Calculations
This Advanced Tableau course provides next-level training to be able to prep and display data in an efficient way. In this course, you’ll utilize Tableau to break down and solve the types of business problems that BI analysts and financial analysts typically face. This course will open the hood of Tableau’s SQL processing to give you a deeper understanding of how these calculations work. You’ll also be applying what you learn to 7 different business scenarios, which we hope you’ll publish into a Tableau Public profile to show off your work. By the end, you’ll have a deeper understanding of Tableau and the confidence to tackle a huge variety of problems. Upon completing this course, you will be able to: • Define level of detail and other critical concepts • Identify the grain and level of detail of a data set • Troubleshoot common errors • Apply fixed, include, and exclude LOD calculations to business scenarios • Identify how different LODs are affected by context and dimension filters • Compare LOD calculations to table calculations This Tableau course is perfect for professionals who have a solid understanding of data analysis and want to expand their skill set to include Tableau’s world-leading visualizations. This course is designed to equip anyone who desires to begin a career in business analysis—or other roles that require displaying and analyzing data sets—with the advanced skills to create dynamic data-viewing experiences.
Coursera
Control Page Access
In today's collaborative work environment, unauthorized access to sensitive pages can expose confidential information, create costly data breaches averaging $4.88 million in damages, and disrupt team workflows. This intermediate-to-advanced course equips IT managers and team leaders with essential skills to protect shared pages while maintaining productive collaboration. You'll learn to identify when page-level restrictions are necessary—whether protecting confidential information or managing work-in-progress content—and discover how targeted access controls address real-world security challenges without over-restricting your teams. Through interactive lessons and hands-on practice, you'll confidently assign editor and viewer roles, verify that restrictions are properly applied, and implement access policies that scale with your organization's growth. By the end of this course, you'll be able to make informed decisions about page access and apply controls that strengthen security, clarify accountability, and enable your teams to work together securely and efficiently.