The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Coursera
Build Client Rapport
Build Client Rapport is an intermediate-level course designed for sales professionals who want to establish strong, natural connections with clients from the first interaction. Because trust is often formed early in a conversation, the course focuses on practical, repeatable techniques that help sellers create comfort, credibility, and openness quickly, without sounding scripted or forced. Across two focused lessons, learners explore three rapid-rapport techniques: mirroring, small-talk alignment, and shared experiences. Learners examine how these behaviors shape first impressions, influence client engagement, and affect the quality of discovery conversations. The course then shifts to application, guiding learners through simulated first-meeting scenarios where they practice opening conversations and demonstrating rapport within the first two minutes. Through short videos, readings, guided practice, and targeted assessments, learners develop rapport-building habits they can apply in real sales conversations. By the end of the course, learners will be able to identify effective rapport techniques and apply them to create stronger client connections from the start.
L&T EduTech
BIM Fundamentals for Engineers
In this course, we will explore the foundational principles of Building Information Modeling (BIM) and its practical applications, starting with the evolution of engineering from traditional 2D drawings to the shift towards object-based modeling, which forms the core of BIM. This understanding sets the stage for examining real-world implementations across diverse sectors including airports, residential and commercial buildings, water treatment plants, substations, transportation, and material handling facilities. We begin with BIM fundamentals through case studies demonstrating its role in enhancing efficiency and collaboration in complex projects. Moving forward, our focus shifts to Design Authoring workflows aligned with ISO 19650 standards, preparing participants for hands-on experience with Autodesk Revit. We explore Revit's user interface comprehensively, covering menus, ribbons, and key concepts such as Revit extensions, parameters, worksets, phases, design options, schedules, annotations, and sheet creation. Finally, participants delve into practical BIM modeling within Revit across architecture, structural, and MEP disciplines, equipping them with essential skills to create detailed and integrated BIM models across disciplines. Join us on this journey to master BIM fundamentals and discover its transformative potential in engineering and construction. Target Learners: • Undergraduate students of Civil Engineering, Electrical Engineering & Mechanical Engineering • Post-Graduate Students in Construction Management. • Practicing Engineers involved in BIM in construction. • Faculties in Civil, Electrical & Mechanical • Industry professionals working in construction and BIM • Project managers and consultants in construction and infrastructure development sectors. Prerequisites: • Basic knowledge of Construction • Familiarity with Construction Management • Understanding of Construction Practices Hardware Prerequisites: Minimum Entry level configuration as follows: 1. Operating System: 64-bit Microsoft® Windows® 10 or Windows 11 2. CPU Type: Intel® i-Series, Xeon®, AMD® Ryzen, Ryzen Threadripper PRO. 2.5GHz or Higher. 3. Memory: 8 GB RAM 4. Video Display: 1280 x 1024 with true color (Minimum) 5. Disk Space: 30GB free disk space Software Prerequisites: • Install Revit 2020 and higher versions for this course
ESSEC Business School
L'excellence opérationnelle en pratique
Lean, Six Sigma, PDCA, Kaizen, Juste à temps, Kanban sont des termes gestionnaires que nous entendons très souvent dans le vocable des entreprises d’aujourd’hui. Ils ont en commun leur finalité, celle de l’excellence opérationnelle. D’origine japonaise et diffusées depuis dans le monde entier, les techniques d’Excellence Opérationnelle servent la qualité et l’amélioration continue. Mais l’Excellence Opérationnelle ne se résume pas à une boîte à outils, c’est avant tout une culture et une posture managériale qui vise l’excellence en permanence. En partenariat avec la chaire Innovation Managériale et Excellence Opérationnelle (IMEO) de l’ESSEC, des professionnels de l’Excellence Opérationnelle issus de deux groupes industriels internationaux, Orano et Renault-Nissan Consulting, nous présentent les principaux outils de l’Excellence opérationnelle avec toute leur expérience. A la fin de ce Mooc, vous saurez : - Expliquer ce que recouvre la notion d’Excellence Opérationnelle - Mobiliser les démarches et outils de l’Excellence Opérationnelle - Intégrer l’Excellence Opérationnelle dans les démarches managériales et les projets de l’entreprise Bon MOOC et profitez bien de l’expérience des professionnels des entreprises Orano et Renault-Nissan Consulting.
Rutgers the State University of New Jersey
Generative AI & Governmental Financial Reporting
This course explores how Generative AI, particularly Large Language Models (LLMs), can transform governmental reports and accounting practices. You will learn how AI can optimize financial data extraction, improve decision-making, and enhance the efficiency of accounting processes. The course addresses key questions such as: • How can LLMs be used to process and analyze financial reports? • What are the challenges of implementing AI in accounting? • How can AI-driven frameworks improve accuracy and efficiency in financial reporting? By the end of the course, you’ll understand how AI-powered tools can automate data extraction, integrate workflows, and improve financial decision-making. This course is designed for: • Accounting and finance professionals looking to integrate AI into their workflows. • Governmental financial analysts and auditors handling large datasets. • AI and data science professionals interested in applications of LLMs in financial reporting. • Students and researchers in accounting, finance, or AI-related fields. Learners with any background are welcome. However, Basic knowledge of accounting principles and financial reporting, familiarity with AI concepts and programming (e.g., Python) are recommended.
Johns Hopkins University
Importing Data in the Tidyverse
Getting data into your statistical analysis system can be one of the most challenging parts of any data science project. Data must be imported and harmonized into a coherent format before any insights can be obtained. You will learn how to get data into R from commonly used formats and harmonizing different kinds of datasets from different sources. If you work in an organization where different departments collect data using different systems and different storage formats, then this course will provide essential tools for bringing those datasets together and making sense of the wealth of information in your organization. This course introduces the Tidyverse tools for importing data into R so that it can be prepared for analysis, visualization, and modeling. Common data formats are introduced, including delimited files, spreadsheets and relational databases, and techniques for obtaining data from the web are demonstrated, such as web scraping and web APIs. In this specialization we assume familiarity with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.
Alex Genadinik
Introduction to Stablecoins: How And When To Use Them
Stablecoins have become one of the most widely used and important innovations in the entire cryptocurrency ecosystem. They power global payments, support trillions in trading volume, provide stability in the highly volatile crypto markets, and act as foundational building blocks in decentralized finance (DeFi). Yet many people still lack a clear understanding of what stablecoins really are, how they work, and what risks they carry. This course provides a comprehensive and beginner-friendly introduction to stablecoins. You will learn the core concepts behind price stability, how pegging mechanisms operate, and why different stablecoins behave differently under market stress. We will explore the major types of stablecoins, including fiat-backed stablecoins, crypto-collateralized stablecoins, and algorithmic stablecoins, using real examples such as USDT, USDC, DAI, FRAX, and others. You will see how each model attempts to maintain stability, what collateral structures support them, and why some designs are considered more reliable than others. Beyond the technical mechanisms, the course explains the practical benefits that have led to rapid global adoption. You will learn how stablecoins are used for international payments, trading, yield generation, remittances, and everyday transactions. You will also understand why traders rely on stablecoins as safe havens during high volatility and how stablecoins enable deeper liquidity in crypto markets. Just as importantly, the course covers the risks that every user should understand. We will discuss reserve transparency, regulatory considerations, depegging events, smart contract vulnerabilities, liquidity issues, and the specific weaknesses that caused several well-known algorithmic stablecoins to fail. By the end of the course, you will know how to evaluate stability, read transparency reports, identify warning signs, and choose stablecoins that match your goals and risk tolerance. No prior crypto experience is required. The course is designed to give beginners a clear, structured foundation so they can navigate stablecoins with confidence and make informed decisions in both personal and professional contexts. Invest in your future! Enroll today!
Google Cloud
Google Workspace Mail Management 日本語版
「Google Workspace Mail Management」は、Google Workspace Administration シリーズの 4 つ目のコースです。 このコースでは、迷惑メール、なりすまし、フィッシング、マルウェア攻撃から組織を保護する方法を学びます。メールのコンプライアンスを設定するほか、組織のデータ損失防止（DLP）の仕組みを実現する方法、使用可能なメール ルーティング方法、送信者を許可リストに登録したりブロックしたりする方法についても学びます。さらに、受信および送信ゲートウェイ、サードパーティ サービスによるメールのアーカイブ、Vault へのジャーナリングなどのメール オプションについての理解も深めます。
University of Michigan
Translating Research to Patients
The second phase of translational research — known as “T2” — assesses the value of applying discoveries to clinical practice, which leads to the development of evidence-based guidelines. This course focuses on clinical trials, the value of applying discoveries to clinical practice, and best practices for conducting research. You’ll see examples of human subjects research through clinical trials that have been translated into practice and, later, into basic scientific discoveries. You’ll also discuss the role of the federal government in supporting and regulating translational research conducted on humans. This is the third course of five in the “Translational Science” series.
Coursera
Vision Models: Train and Evaluate
This short course gives you practical experience training and evaluating computer vision models. You’ll learn how to build image preprocessing pipelines, apply data augmentation, and train deep learning models such as CNNs and Vision Transformers. You’ll also learn to evaluate performance using metrics such as mean Average Precision (mAP), Intersection over Union (IoU), precision, and recall, and to use error analysis to understand failure patterns. Through short videos, focused readings, hands-on labs, and guided coaching, you’ll practice real job tasks such as writing TensorFlow data loaders, training a Vision Transformer on plant-disease images, computing per-class AP and mAP, and comparing results across IoU thresholds. By the end, you’ll have a complete workflow you can adapt to your own projects and use to demonstrate your skills.
Microsoft
Data Analytics and Machine Learning for Big Data
This advanced course teaches machine learning and AI techniques for big data systems. Learners will build end-to-end ML pipelines with PySpark ML, implement supervised and unsupervised models, and apply NLP techniques at scale. The course also explores deep learning, distributed training, and integrating Generative AI into big data workflows. By the end of this course, you will be able to: - Implement ML pipelines using PySpark ML - Build supervised, unsupervised, and recommendation models - Apply NLP and text analytics to large datasets -Integrate Generative AI and LLMs with big data systems Tools & Software: PySpark ML, PyTorch, TensorFlow, Azure Machine Learning, Azure OpenAI Service Skills: Machine learning, NLP, Deep learning, Generative AI, Model evaluation
University of Michigan
Web Application Technologies and Django
In this course, you'll explore the basic structure of a web application, and how a web browser interacts with a web server. You'll be introduced to the Hypertext Transfer Protocol (HTTP) request/response cycle, including GET/POST/Redirect. You'll also gain an introductory understanding of Hypertext Markup Language (HTML), as well as the overall structure of a Django application. We will explore the Model-View-Controller (MVC) pattern for web applications and how it relates to Django. You will learn how to deploy a Django application using a service like PythonAnywhere so that it is available over the Internet. This is the first course in the Django for Everybody specialization. It is recommended that you complete the Python for Everybody specialization or an equivalent learning experience before beginning this series.
Coursera
Using GenAI for Tailored Customer Emails
How often have you received generic, uninspiring email content that makes you hit the spam or trash button as quickly as possible? Most of us don't often get to the end of these emails either, right? Personalized communication is key to engaging customers and driving business success! This intermediate course is designed for professionals who want to leverage Generative AI (GenAI) tools to draft and optimize the process of tailoring emails for unique customer segments. Through a series of practical lessons and a hands-on activity, you will gain the skills you need to effectively use GenAI to elevate your email marketing content. Consider the potential impact this can have on personalizing emails that truly engage your audience, not to mention that increase in efficiency! This intermediate-level short course was created to help email marketers and customer engagement professionals master the art of creating tailored customer emails using generative AI tools to enhance marketing efforts and customer relationships. By completing this course you'll be able to you'll be able to draft and optimize customized emails for customers using GenAI tools. You'll be equipped to immediately apply these transferrable skills to boost your customer engagement and satisfaction, through highly personalized communication. By the end of this 3-hour course, you will be able to: - Review the features and best practices of GenAI tools for tailoring customer emails. - Develop tailored email content for customer segments using GenAI. In the continuously evolving arena of AI, this course is unique because it leverages one of Generative AI's most powerful features—personalization! You'll gain hands-on experience using popular AI and email marketing tools, learning to apply theese effectively to real-world email marketing scenarios. To be successful in this course and get the most from the content, you should have a basic understanding of email marketing and tools (such as Hubspot, GMass, Mailchimp, SurveyMonkey, etc.). Familiarity with generative AI is beneficial but not strictly required, especially if you have basic user experience (For instance, you're aware that ChatGPT generates human-like text from prompts). You will need: - ChatGPT (free or paid version) - An email marketing tool (this course uses Hubspot, however, you may use an email marketing tool of your choice)
Tally Education and Distribution Services Private Limited
Principles of Accounts Payable and Receivable Management
This course is for those interested in starting a career in bookkeeping. The course builds on the knowledge and skills covered in the first course in this professional certificate, Fundamentals of Accounting and Reporting, and dives deeper into accounts payable and receivable management. You will not only learn concepts related to accounts payable and receivable, but also demonstrate the basic concepts of computerized accounting using Tally. Tally is a revolutionary product which has been created with greater flexibility and a new look and feel. By the end of the course, you will be able to: - Classify inventory - Manage accounts receivable and accounts payable - Manage purchase and sales orders - Track costs of purchase - Manage cost and profit centers - Create and maintain budgets using TallyPrime - Generate reports No prior experience in bookkeeping is required. To be successful in this course, you should have completed the first course in this program, Fundamentals of Accounting and Reporting, or have the equivalent skills and knowledge.
Coursera
Pneumonia Classification using PyTorch
In this 2-hour guided project, you are going to use EfficientNet model and train it on Pneumonia Chest X-Ray dataset. The dataset consist of nearly 5600 Chest X-Ray images and two categories (Pneumonia/Normal). Our main aim for this project is to build a pneumonia classifier which can classify Chest X-Ray scan that belong to one of the two classes. You will load and fine tune the pretrained EffiecientNet model and also to create a simple pytorch trainer to train the model. In order to be successful in this project, you should be familiar with python, convolutional neural network, basic pytorch. This is a hands on, practical project that focuses primarily on implementation, and not on the theory behind Convolutional Neural Networks. 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.
Coursera
Создаем аккаунт для бизнеса в Twitter
В этом проекте вы научитесь создавать аккаунт для бизнеса в Twitter. Примечание. Этот курс изначально создан для учащихся из Северной Америки. На данный момент мы адаптируем его и для других регионов.
University of Michigan
Introduction to Time Value of Money (TVM)
The strength of finance is that it takes a structured approach to decision making, with one key building block underlying all decisions — understanding the value of time, or the Time Value of Money (TVM). In this course, we will develop this building block using introductory, and simple, applications. We will learn about the Time Value of Money (TVM), Simple Future Value (FV) , Simple Present Value (PV) , Future Value of Annuity, Loans, compounding, and Valuing Perpetuities. We will introduce the framework in a carefully structured and replicable way to prepare you to explore more advanced applications in the rest of the specialization. In the follow-on courses, we will expand the applications to more complex real-world decisions. After completing this course, you will have an understanding of how the value of money changes over time. You will understand the implications of all your financial decisions, including saving for the future through different channels and borrowing for future needs. You will leave with the practical knowledge needed to make informed decisions on a wide range of financial decisions. This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization.