The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
University of California, Santa Barbara
Revenue and Expense Recognition
By the end of this course, you’ll be able to analyze how revenue adjustments, expenses, and long-term assets are recognized and reported under Generally Accepted Accounting Principles (GAAP). You’ll calculate and record sales returns, discounts, and allowances, distinguish between service, merchandising, manufacturing, and startup expenses, and evaluate how tangible and intangible assets affect financial statements. You’ll also determine gains and losses on asset disposals and assess when long-term assets must be written down for impairment. Throughout the course, you’ll move beyond definitions and apply accounting treatment to realistic business scenarios, strengthening your ability to interpret balance sheets and income statements with confidence. What makes this course unique is its applied, decision-focused approach. Rather than memorizing rules, you’ll learn how accounting choices impact financial performance, reporting transparency, and business valuation. By the end, you’ll have a stronger command of asset accounting and financial reporting mechanics—skills essential for aspiring CPAs, accounting professionals, and finance-focused business leaders.
University of Illinois Urbana-Champaign
Lactation Biology
Lactation and especially milk, which is the product of that unique mammalian process, are routinely encountered within our daily lives. Nevertheless, they often are poorly understood by many, even including many who are engaged in the business of producing milk. The overall course goal is to introduce fundamental concepts that form the basis for understanding the biology of lactation, the biology of the mammary gland, and the products of that important physiological process. As a learner in this course, you will be provided with a series of easily understood presentations that collectively will help you build a foundation for greater understanding of lactation. You will be able to engage with other learners so that you can extend your learning beyond the video presentations. Ultimately, you will be able to construct your own mental model for understanding the wide range of topics that relate to the biology of lactation. Upon completion of the course, you will be prepared to expand your knowledge and understanding of lactation from other sources and experiences as you pursue your individual interests. Before you start the course, I suggest that you identify a question or several questions about lactation that you already have on your mind. This could be from your own experiences, something you read about or saw, or something you have wondered about. Write down your question(s) and use that to help you decide how to engage with the content of this course. You might engage with the modules in the order they are presented, or start with a module that is of particular interest to you, or pick and choose modules in any order. I encourage you to engage in all of the types of learning activities that this course has to offer, including but not limited to, the discussion forums, quizzes, peer-review assignments, and concept maps and other learning aids.
L&T EduTech
Components of Hydropower Structures
This course provides a comprehensive exploration of hydropower engineering, covering fundamental components, electromechanical systems, and specialized construction techniques. It begins by detailing the various parts of a hydropower project, from headworks and water conveyance to dams and associated structures, including real-world examples from Indian dams. The course then transitions to the mechanical and structural aspects, examining retaining walls, turbines, valves, and maintenance equipment. Finally, it delves into the intricacies of tunnel construction, covering site investigation, support systems, excavation methods, operational logistics, and safety protocols, offering a holistic understanding of hydropower infrastructure development. Target Learners: Undergraduate students of Civil Engineering Post-Graduate Students of Integrated Water Resources Management Post-Graduate Students of Structural Engineering Faculties of Civil Engineering Domain Working Professionals in the above domain & other aspiring learners Pre-requisites: Fundamental knowledge on Fluid Mechanics, Applied Hydraulics, Water Resources Engineering Exposure to Indian codal standards
Logical Operations
Crystal Reports: Formulas, Parameters, and Groups
In this course, you'll continue developing your data-reporting skills in Crystal Reports by using creating, editing, and filtering data in reports. You'll also build parameterized reports and group report data to make the process of interpreting data easier. This is the second course in a multi-course Specialization. All of the courses in this Specialization require that you have SAP Crystal Reports 2020 installed. You also need to have an installation of Office 2019 apps or later, particularly Access. The course setup instructions provided in the first course go into more detail about the hardware and software requirements.
EDUCBA
AI Foundations with Python: Build & Visualize
By completing this beginner-friendly course, learners will be able to set up Python environments, manipulate data using NumPy, and create insightful visualizations with Matplotlib and Seaborn. Designed for those starting their journey in Artificial Intelligence, the course ensures students build a strong computational foundation before progressing to advanced AI concepts. Through step-by-step guidance, learners will first configure Anaconda Navigator and Jupyter Notebook for a seamless workflow, then apply NumPy for array functions, indexing, and filtering techniques essential in AI data handling. Moving forward, they will implement Matplotlib for basic plots and transition to Seaborn for high-level, visually appealing statistical visualizations, including scatter plots, heatmaps, and box plots. What makes this course unique is its practical, project-oriented approach that blends setup, numerical computation, and data visualization into one cohesive learning path. By the end, learners will have both the technical skills and the confidence to explore real-world AI projects, effectively preparing them for more advanced machine learning and deep learning studies.
Coursera
GenAI for Customer Communication
In this course, "AI-Driven Customer Communication: Enhancing Engagement and Personalization," you’ll learn practical AI techniques, with personal case studies and experiences, to deliver personalized, real-time customer interactions that drive satisfaction and loyalty. You'll learn essential AI techniques to enhance customer engagement and satisfaction. Understand the basics of AI in customer communication, develop effective personalization strategies, and master data-driven decision-making. You'll explore specific techniques like AI-driven chatbots for real-time customer support, predictive analytics to anticipate customer needs, and sentiment analysis to evaluate customer feedback. Learn how to apply personalized product recommendations to improve conversion rates and use AI-powered customer journey mapping to optimize every interaction. With hands-on learning, you'll gain practical skills such as implementing chatbots in customer service scenarios, using predictive tools to reduce churn, and analysing feedback to enhance customer satisfaction. This course is designed for Customer Service Managers, Marketing Professionals, Business Analysts and Digital Transformation Leaders. It is ideal for individuals looking to leverage AI to enhance customer communication strategies, improve customer engagement, and drive satisfaction across various touchpoints. Professionals seeking to stay ahead in the evolving landscape of customer service and marketing will benefit from this course's practical insights and hands-on approach. To get the most out of this course, participants should have a basic understanding of AI technology and its applications in business. Familiarity with customer engagement concepts and customer service strategies will be helpful, as these form the foundation for the techniques explored in the course. Some prior experience with digital communication tools and platforms is also recommended to fully grasp the AI-driven techniques discussed. By the end of this course, learners will be able to analyze key concepts and benefits of AI in customer communication, enabling them to understand how AI can drive business growth. Participants will also gain the ability to identify cutting-edge techniques for AI-driven personalization, allowing them to tailor customer experiences more effectively. Additionally, they will be equipped to apply AI tools for enhancing customer feedback analysis and journey mapping, enabling more informed, data-driven decision-making in real-world business scenarios.
Imperial College London
Survival Analysis in R for Public Health
Welcome to Survival Analysis in R for Public Health! The three earlier courses in this series covered statistical thinking, correlation, linear regression and logistic regression. This one will show you how to run survival – or “time to event” – analysis, explaining what’s meant by familiar-sounding but deceptive terms like hazard and censoring, which have specific meanings in this context. Using the popular and completely free software R, you’ll learn how to take a data set from scratch, import it into R, run essential descriptive analyses to get to know the data’s features and quirks, and progress from Kaplan-Meier plots through to multiple Cox regression. You’ll use data simulated from real, messy patient-level data for patients admitted to hospital with heart failure and learn how to explore which factors predict their subsequent mortality. You’ll learn how to test model assumptions and fit to the data and some simple tricks to get round common problems that real public health data have. There will be mini-quizzes on the videos and the R exercises with feedback along the way to check your understanding. Prerequisites Some formulae are given to aid understanding, but this is not one of those courses where you need a mathematics degree to follow it. You will need basic numeracy (for example, we will not use calculus) and familiarity with graphical and tabular ways of presenting results. The three previous courses in the series explained concepts such as hypothesis testing, p values, confidence intervals, correlation and regression and showed how to install R and run basic commands. In this course, we will recap all these core ideas in brief, but if you are unfamiliar with them, then you may prefer to take the first course in particular, Statistical Thinking in Public Health, and perhaps also the second, on linear regression, before embarking on this one.
Imperial College London
Immunology: Innate Immune System
Our immune system relies on an innate and an adaptive arm that communicate and collaborate to provide us with an optimal response against pathogens. This course focuses on our innate immunity which provides us our first, fast and inherited defence against infections. In this course, you will take a closer look at the mechanisms and cellular components involved in this swift response that occurs within minutes of exposure to a threat. Throughout the course, and guided by our active researchers, you will have opportunities to recognise its key protective mechanisms and to explain their importance for our overall health. You will learn about the mechanisms it uses to inform our adaptive immune system of the presence of a threat, and understand how some environmental factors, such as our own internal microbiome, influences it. Finally, you will have opportunities to reflect on current related issues and controversies in this fascinating field of research.
Packt
C# Object-Oriented Programming for Beginners in C# and .NET
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’ll learn the fundamentals of Object-Oriented Programming (OOP) in C# and .NET. By the end of the course, you’ll have a solid understanding of core OOP principles such as abstraction, encapsulation, inheritance, and polymorphism, all essential for building robust applications. This course is designed for beginners and will guide you step by step, helping you grasp C# classes, fields, methods, interfaces, inheritance, and more. The course starts with an introduction to the basics of OOP and helps you get comfortable with C# by building a simple project. You will learn how classes and objects play a role in structuring applications and dive deeper into fields, methods, and constructors that form the foundation of C# programming. Throughout the course, you will work through practical coding assignments that reinforce your understanding. In the subsequent sections, the course explores advanced concepts like interfaces, inheritance, and polymorphism. You’ll understand how to create and implement interfaces, how inheritance allows for code reuse, and how polymorphism enhances the flexibility of your code. With each section, you’ll build on the concepts learned earlier, gaining more confidence in your programming skills. This course is perfect for anyone starting with C# or OOP. It’s tailored for beginners and requires no prior experience in programming. By the end, you will have the ability to develop object-oriented applications using C# and .NET, laying a solid foundation for further learning in software development.
Eindhoven University of Technology
Process Mining: Data science in Action
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action". The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains. This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments. The course covers the three main types of process mining. 1. The first type of process mining is discovery. A discovery technique takes an event log and produces a process model without using any a-priori information. An example is the Alpha-algorithm that takes an event log and produces a process model (a Petri net) explaining the behavior recorded in the log. 2. The second type of process mining is conformance. Here, an existing process model is compared with an event log of the same process. Conformance checking can be used to check if reality, as recorded in the log, conforms to the model and vice versa. 3. The third type of process mining is enhancement. Here, the idea is to extend or improve an existing process model using information about the actual process recorded in some event log. Whereas conformance checking measures the alignment between model and reality, this third type of process mining aims at changing or extending the a-priori model. An example is the extension of a process model with performance information, e.g., showing bottlenecks. Process mining techniques can be used in an offline, but also online setting. The latter is known as operational support. An example is the detection of non-conformance at the moment the deviation actually takes place. Another example is time prediction for running cases, i.e., given a partially executed case the remaining processing time is estimated based on historic information of similar cases. Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development. The course uses many examples using real-life event logs to illustrate the concepts and algorithms. After taking this course, one is able to run process mining projects and have a good understanding of the Business Process Intelligence field. After taking this course you should: - have a good understanding of Business Process Intelligence techniques (in particular process mining), - understand the role of Big Data in today’s society, - be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification, - be able to apply basic process discovery techniques to learn a process model from an event log (both manually and using tools), - be able to apply basic conformance checking techniques to compare event logs and process models (both manually and using tools), - be able to extend a process model with information extracted from the event log (e.g., show bottlenecks), - have a good understanding of the data needed to start a process mining project, - be able to characterize the questions that can be answered based on such event data, - explain how process mining can also be used for operational support (prediction and recommendation), and - be able to conduct process mining projects in a structured manner.
Coursera
Decide with Data: Boost Patient Outcomes
Did you know that healthcare organizations using data-driven decision making see 15-20% improvements in patient outcomes? Yet many healthcare professionals struggle to translate data into actionable insights that truly impact care delivery. This Short Course was created to help healthcare data analysts accomplish evidence-based decision making that directly improves patient outcomes. By completing this course, you'll be able to confidently explain analytical approaches to clinical teams, systematically evaluate care options using structured frameworks, and distinguish between statistically interesting and practically meaningful findings that warrant action. By the end of this course, you will be able to: - Explain the difference between descriptive and prescriptive analytics - Apply a decision matrix to evaluate options and recommend a course of action - Understand the concept of practical significance in data analysis This course is unique because it connects foundational analytics concepts directly to bedside scenarios, helping you bridge the gap between data science and patient care in ways that resonate with clinical teams. To be successful in this project, you should have a background in basic healthcare operations and familiarity with quality improvement processes.
Coursera
Financial Forecasts: Learn from Errors
Financial Forecasts: Learn from Errors is an advanced course for financial analysts and planners who want to move beyond just building models to building better models. In the real world, forecasts are rarely perfect. This course teaches you the critical skill of learning from those imperfections to drive continuous improvement and predictive accuracy. You will learn to perform a root cause analysis on failed models, pinpointing whether errors stem from flawed assumptions, bad data, or broken logic. Through a hands-on analysis of a failed retail model, you'll write a professional lessons-learned memo. Next, you'll shift focus to dissecting success, analyzing how a project overcame cost overruns, and synthesizing those learnings into a reusable best-practice checklist. The course culminates in a final project where you will use these new skills to create a comprehensive forecasting improvement plan. By the end, you won't just be a model builder; you'll be a model strategist, equipped to enhance the reliability and credibility of your team's financial forecasts.
Coursera
GenAI for Digital Marketing Specialists
The GenAI Academy offers an engaging course designed specifically for Digital Marketing Specialists, focusing on how Generative Artificial Intelligence (GenAI) can revolutionize marketing strategies. This program provides you with essential knowledge and skills to creatively and effectively leverage GenAI in your projects. This course is designed for team leaders and managers seeking to enhance team productivity and creativity with GenAI, digital marketing specialists focused on improving content creation and campaign management, and career transitioners aiming to specialize in digital marketing and stay competitive by mastering GenAI technologies. While no prior AI expertise is needed, familiarity with popular social media platforms (e.g., Facebook, Instagram, Twitter, LinkedIn), strong communication and data analysis skills, and proficiency in content creation will enhance your learning experience. Embracing creativity and having a solid understanding of fundamental marketing concepts are also beneficial. Upon successful completion of the curriculum, students at any proficiency level will be well prepared to seamlessly integrate GenAI into their marketing strategies, leading to increased efficiency, productivity and favorable outcomes in their digital marketing endeavors.
Alex Genadinik
Pricing Strategies
Maximize your profit from each customer with accurate pricing! This course will teach you: Product pricing strategy Service pricing strategy Sales negotiation How to maximize your LTV (lifetime customer value) These are the three essential components of making sure that you get the most out of every client. Most first-time entrepreneurs struggle with choosing the right price for their business. But the key to maximizing revenue from each customer is the LTV (lifetime customer value). In this course, in addition to explaining how to price different products, I explain how to get those same customers to come back to your business many more times, and buy many additional times from you, often increasing revenue by thousands of percent. This course also teaches you business negotiation skills, which can maximize your profit. PRICING STRATEGY CASE STUDY The course contains a pricing case study of one of my products that has been sold for as little as $20 and as much as $5,000 for the exact same product. I explain complete negotiation tactics around it. If you have a new business or a product that you are not sure how to price, get this course today and learn how to find an ideal price for your product or service. INSTRUCTOR BACKGROUND I've been an entrepreneur for 15+ years, have coached 1,000+ entrepreneurs in person, taught 100,000+ students, impacted millions of entrepreneurs worldwide creating 6 and 7-figure businesses in the process, and I would love to help you. I am an expert growth marketer, and I create winning marketing strategies for my clients all the time. Now it is your turn to grow your business and fulfill your dreams. BONUSES INCLUDED * Lots of extra freebies, downloadable worksheets, and exercises to make the course more interactive and valuable * Personal invitation to my Facebook community after you complete the course * My list of 50 business-success skills when you complete the course * Be entered to get chosen for my student of the month status and have your business featured RESPONSIVE AND CARING INSTRUCTOR: WORLD-CLASS STUDENT SUPPORT If you have questions, know that I am here to help! I answer 99% of student questions within 24 hours. Many students tell me that other instructors don't respond. Well, I do because 1) I care about my students. 2) I feel a responsibility to make sure that students get their money's worth from the course. Invest in your future. Enroll now.
Google Cloud
AI 인프라: Cloud TPU
Cloud TPU 과정에 오신 것을 환영합니다. 다양한 시나리오에서 TPU의 장단점을 살펴보고 여러 TPU 가속기를 비교하여 적합한 것을 선택하는 데 도움을 드리겠습니다. 이 과정을 통해 AI 모델의 성능과 효율성을 극대화하는 전략을 배우고 유연한 머신러닝 워크플로에 있어 GPU/TPU 상호 운용성이 얼마나 중요한지 이해하게 될 것입니다. 흥미로운 콘텐츠와 실용적인 데모를 통해 TPU를 효과적으로 활용하는 방법을 단계별로 안내해 드리겠습니다.
Università Bocconi
Private Equity and Venture Capital
The course deals with the analysis of the private equity and venture capital business. Over the course, students will be provided with a deep understanding of the mechanism underpinning the creation and/or development of a firm and the financial support it can get from the financial system through venture capital investment. The course tries to discover how special financial intermediaries (called private equity investors) finance through equity companies belonging to different stages of their life-cycle, starting from the very beginning (startup and early stage) to a more mature phase (i.e. expansion, mature age, etc.) or also staying into crises and decline. Private equity (named venture capital when the company is in the first phases of its life cycle) deals with very different activities, such as scouting, advisory, deal-making, valuation, and financing as financial intermediaries see it. COURSE SYLLABUS The course is made up of four different modules: WEEK 1 - Introduction to Private Equity and Venture Capital WEEK 2 - Discovering Private Equity Investors: Legal Issues and Taxation WEEK 3 - Management of Private Equity and Venture Capital Funds WEEK 4 - Company Valuation And Deal Making In Private Equity Settings WEEK 5 - Final Test Throughout the course, guest speakers and practitioners will be interviewed to provide some examples of concrete applications of the contents presented. RECOMMENDED BACKGROUND An understanding of the basic concepts of corporate financing accounting principles is required, while prior knowledge of private equity and venture capital is not required however it is recommended, as this is a course designed to introduce you to the fundamental concepts in private equity and venture capital.