The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
University of Illinois Urbana-Champaign
Forecasting Financial Statements & Valuation for Accountants
The objective of this course is to provide you with the knowledge and skills necessary to analyze, interpret, understand and use financial information to make informed decisions. We will discuss financial reporting from a user’s perspective, use a variety of tools to break apart financial reports into meaningful units for analysis, forecast financial statements, and value a firm. This course is intended to give you exposure to the issues facing users of financial statements. You will better understand your role in the financial reporting process if you know how the financial statements will ultimately be used. Beyond the Financials: Insights, Analysis and Valuations will require you to think critically about issues for which there can be more than one “correct” answer. Hence, your analysis and conclusions must be based on sound assumptions and well-constructed analysis and arguments.
EDUCBA
Linear Regression & Supervised Learning in Python
This hands-on course empowers learners to apply and evaluate linear regression techniques in Python through a structured, project-driven approach to supervised machine learning. Designed for beginners and aspiring data professionals, the course walks through each step of the regression modeling pipeline—from understanding the use case and importing key libraries to analyzing variable relationships and predicting outcomes. In Module 1, learners will identify, describe, and prepare the foundational elements of a machine learning project. Through univariate and graphical analysis, they will recognize distribution patterns, outliers, and data characteristics critical to model readiness. In Module 2, learners will analyze variable relationships, construct a regression model, and evaluate its predictive performance using standard metrics and visualizations. By the end of the course, learners will confidently interpret model results and validate them against actual outcomes—equipping them with the core skills to build and assess linear regression models using Python. This course blends practical demonstrations, clear conceptual explanations, and structured assessments—including practice and graded quizzes aligned with Bloom’s Taxonomy—to promote deep, outcome-oriented learning.
EDUCBA
Oracle PL/SQL: Design & Optimize Subprograms
By the end of this course, learners will be able to design, implement, and manage explicit cursors, apply exception handling strategies, build reusable PL/SQL procedures, and construct stored functions that integrate seamlessly with SQL queries. Through a structured, hands-on approach, the course equips students to demonstrate control over multi-row data retrieval, apply robust error management, and evaluate when to use procedures versus functions for optimal performance. Learners will benefit by gaining practical coding experience with real-world examples of parameter handling (IN, OUT, IN OUT), cursor management, and function creation. This ensures they can optimize database applications for reliability, maintainability, and scalability. What makes this course unique is its step-by-step progression from foundational concepts to advanced implementations, supported by practical demonstrations and targeted quizzes that reinforce mastery at every stage. Unlike generic tutorials, this program combines conceptual clarity with industry-focused use cases, preparing learners for real-world database programming challenges in Oracle environments.
University of Colorado Boulder
Averaged-Switch Modeling and Simulation
This course can also be taken for academic credit as ECEA 5705, part of CU Boulder’s Master of Science in Electrical Engineering degree. This is Course #1 in the Modeling and Control of Power Electronics course sequence. The course is focused on practical design-oriented modeling and control of pulse-width modulated switched mode power converters using analytical and simulation tools in time and frequency domains. A design-oriented analysis technique known as the Middlebrook's feedback theorem is introduced and applied to analysis and design of voltage regulators and other feedback circuits. Furthermore, it is shown how circuit averaging and averaged-switch modeling techniques lead to converter averaged models suitable for hand analysis, computer-aided analysis, and simulations of converters. After completion of this course, the student will be able to practice design of high-performance control loops around switched-mode power converters using analytical and simulation techniques. We strongly recommend students complete the CU Boulder Power Electronics specialization before enrolling in this course (course numbers provided for students in CU Boulder's MS-EE program): ● Introduction to Power Electronics (ECEA 5700) ● Converter Circuits (ECEA 5701) ● Converter Control (ECEA 5702) After completing this course, you will be able to: ● Explain operation and modeling of switched-mode power converters ● Model open-loop transfer functions and frequency responses ● Design closed-loop regulated switched-mode power converters ● Verify operation of switched-mode power converters by simulations ● Understand the Feedback Theorem principles ● Apply the Feedback Theorem to practical design examples ● Derive averaged switch models of and averaged circuit models of power converters ● Apply averaged-switch modeling techniques to analysis and design and simulations of power converters
Coursera
Frame AI Problems: Objectives to Metrics
Successful AI projects start with clarity, not code. This short, hands-on course helps you turn vague business goals into structured, measurable, and feasible AI problem statements. You’ll learn to evaluate whether your data is ready for modeling, estimate labeling requirements, and identify early risks such as imbalance, poor quality, or limited resources. Using real-world scenarios, you’ll apply the SMART framework to define objectives that are specific, measurable, achievable, relevant, and time-bound. By connecting business outcomes with technical success metrics like precision and recall, you’ll gain the confidence to frame AI projects that deliver measurable impact and align teams from idea to implementation.
Genentech
Data Science in Health Technology Assessment
This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.
IESE Business School
Dominando el arte de escalar y convencer a los inversores
Este curso brinda a los emprendedores aspirantes y en etapa inicial una visión integral de lo que se necesita para lanzar y escalar una startup exitosa. Desde navegar decisiones clave sobre el momento de lanzar un producto y las asociaciones con inversores, hasta dominar el arte del pitch y la valoración, cada módulo ofrece marcos prácticos y ejemplos reales. Al abordar los errores más comunes y resaltar los factores clave de éxito, la serie empodera a los participantes para que piensen de forma estratégica, tomen decisiones informadas y se relacionen con confianza con posibles inversores.
Packt
Computer Programming for Absolute Beginners
Learn essential computer science concepts and coding techniques to kick-start your programming career. By following this course you will gain essential programming skills to enhance your career and expand your technical capabilities. This course guides you through foundational programming concepts, helping you overcome challenges in understanding major constructs across various languages. By mastering these skills, you'll be equipped to learn any programming language and advance your career with confidence. Computer Programming for Absolute Beginners will help you to learn how to program by taking you through the major constructs you will find in any mainstream programming language. The course will guide you through the main building blocks of any programming language with thorough explanations and relevant examples in pseudocode. You will learn the concepts of programming by relatable, real-world examples. After reading this book you will be well equipped to learn any programming language at an accelerated rate. This course is ideal for beginners with no prior programming experience who wish to enter the programming world. It's perfect for those starting their programming studies or anyone eager to learn coding independently. It is also ideal if you have tried to learn a programming language before and struggled. This course is based on material written by an expert author, bringing the depth of a book into a more engaging, interactive format. The core content is delivered through clear, structured text you can read at your own pace, supported by short videos and quizzes to highlight key ideas and test your understanding. By combining the strengths of book learning with interactive assessments, you get the best of both worlds: the depth and clarity of an author’s expertise, plus the flexibility to revisit, practice, and reinforce concepts whenever you need.
Duke University
Interacting with the System and Managing Memory
The final course in the specialization Introduction to Programming in C will teach you powerful new programming techniques for interacting with the user and the system and dynamically allocating memory. You will learn more sophisticated uses for pointers, such as strings and multidimensional arrays, as well as how to write programs that read and write files and take input from the user. Learning about dynamic memory allocation will allow your programs to perform complex tasks that will be applied in the final part of the specialization project: a Monte Carlo simulation for calculating poker hand probabilities.
Packt
Data-Driven Apps with Core Data, ML, and App Architecture
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. In this course, you will dive into building data-driven apps by mastering Core Data, Machine Learning (ML), and app architecture. You’ll learn to create dynamic and efficient apps by integrating these essential technologies. By the end of the course, you’ll have developed hands-on skills in data management, machine learning model deployment, and structuring apps for scalability and performance. You will start by developing a Core Data math game, where you will learn to manage game data, implement high scores, and build interactive game views. The course then moves into converting your Core Data game to Swift Data, refining your understanding of modern data frameworks. Finally, you will explore creating a Titanic survival prediction app using Core ML and Create ML, building a complete end-to-end machine learning project. This course is perfect for anyone looking to understand app architecture and data management in iOS development. The content is ideal for developers aiming to deepen their knowledge of Core Data, Swift Data, and integrating ML models into apps. Prior experience in iOS development and Swift programming is recommended. By the end of the course, you will be able to build and deploy data-driven applications using Core Data, Swift Data, and Core ML, design robust app architectures, implement machine learning models in Swift, and manage app data with modern frameworks like Core Data and Swift Data.
University of Maryland, College Park
Usable Security
This course focuses on how to design and build secure systems with a human-centric focus. We will look at basic principles of human-computer interaction, and apply these insights to the design of secure systems with the goal of developing security measures that respect human performance and their goals within a system.
Universitat Autònoma de Barcelona
El Valle de los Reyes
Este curso va dirigido a todos los amantes de la historia y arqueología, en general, y de manera particular a todos los interesados en egiptología, independientemente de su nivel de conocimiento inicial. El Valle de los Reyes constituye uno de los yacimientos arqueológicos más importantes de Egipto y su estudio, desde diferentes enfoques, resulta muy atractivo para cualquier aficionado o profesional de la egiptología. Con este curso nos proponemos conocer su historia y evolución a lo largo de las dinastías XVIII-XX del Reino Nuevo egipcio, desde su origen hasta su abandono y desmantelamiento. Nos introduciremos en su geología y conservación; estudiaremos su arqueología, llena de descubrimientos emocionantes, de investigaciones que no cesan, y de arqueólogos que, como Howard Carter, asociaron su vida al Valle; conoceremos la organización de los trabajadores de Deir el-Medina que excavaron y decoraron estos hipogeos; estudiaremos parte del material funerario contenido en algunas de sus tumbas, con especial atención a los sarcófagos y ushebtis reales, así como peces procedentes de la tumba de Tutankhamos; conoceremos los principales textps religiosos e iconografía que decoran las tumbas de los reyes. En definitiva, profundizando en el estudio del Valle de los Reyes conseguiremos adentrarnos un poco más en el conocimiento de la cultura y el legado el Antiguo Egipto.
DeepLearning.AI
Повышение эффективности глубоких нейросетей
Этот курс научит вас «магии» повышения эффективности глубокого обучения. Вы изучите сложный механизм работы глубокого обучения, узнаете, какие параметры влияют на его эффективность и сможете систематически получать хорошие результаты. Также вы изучите TensorFlow. По прошествии трех недель вы: — освоите передовые методы создания приложений для глубокого обучения; — научитесь эффективно использовать распространенные «хитрости» работы с нейросетями, включая инициализацию, L2-регуляризацию и регуляризацию методом исключения, пакетную нормализацию и проверку градиента; — научитесь выполнять и применять различные алгоритмы оптимизации, такие как мини-пакетный градиентный спуск, моменты, RMSprop и Adam, а также проверять их сходимость; — освоите передовые методы составления наборов данных для обучения, разработки и тестирования, а также анализа предвзятости и отклонений; — сможете реализовывать нейронную сеть в TensorFlow. Это второй курс специализации «Глубокое обучение».
Packt
Edge Computing Patterns for Solution Architects
Edge computing is transforming how modern enterprises deliver data-driven services, bridging the gap between centralized cloud infrastructures and decentralized edge environments. This course provides a deep understanding of the architectural patterns and design principles needed to create resilient, scalable, and high-performance distributed systems. Through practical exploration, learners will master strategies to design and deploy edge solutions across hybrid and multi-cloud ecosystems. They’ll gain hands-on knowledge of how to balance workloads, manage latency-sensitive applications, and apply industry-tested best practices to real-world use cases. What makes this course unique is its pattern-based approach, built around real-world examples, automation principles, and scalability considerations. It connects theoretical frameworks with proven architectures, ensuring learners can apply what they learn directly to complex enterprise environments. This course is designed for solution architects, enterprise architects, and IT professionals experienced in cloud computing who want to specialize in edge solution design. A foundational understanding of cloud architecture concepts is recommended to get the most from this course.
University of California San Diego
Advanced Algorithms and Complexity
In previous courses of our online specialization you've learned the basic algorithms, and now you are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others. Next we discuss inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice. We finish with a soft introduction to streaming algorithms that are heavily used in Big Data processing. Such algorithms are usually designed to be able to process huge datasets without being able even to store a dataset.
Fundação Instituto de Administração
As Competências do Especialista no Sucesso do Cliente
Nossas boas-vindas ao Curso As Competências do Especialista no Sucesso do Cliente. Neste curso, você aprenderá que o papel de Especialista no Sucesso do Cliente (Customer Success – CS) é multidisciplinar. É preciso entender a fundo o relacionamento com clientes, entender e gerenciar objetivos de negócio, estabelecer o relacionamento entre soluções de tecnologia e negócios, executar análises de mercado e de dados para gerar oportunidades de negócio, além de participar da criação e manutenção de soluções de tecnologia que viabilizem os modelos de negócio com receita recorrente. Ao final deste curso, você será capaz de: - Identificar as principais competências do especialista no sucesso do cliente. - Estabelecer critérios de busca de talentos para a função ou criar um plano para seu próprio desenvolvimento. 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!