The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Packt
Effective Game Design Patterns - Unity 6 Compatible
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'll unlock the full potential of game development by mastering essential design patterns in Unity 6. You’ll learn how to enhance your game’s architecture, optimize performance, and create more scalable and maintainable projects. As you progress, you will dive deep into key design patterns such as Command, Flyweight, Observer, Prototype, Singleton, State, and Object Pool. Each section takes you step-by-step through these concepts, with practical examples and exercises in Unity 6. You'll gain a deeper understanding of the benefits of each pattern and how to implement them effectively in your projects. The course is structured to start with a solid foundation, covering everything from memory optimization with the Flyweight Pattern to implementing complex AI behaviors using the State Pattern. Through hands-on experience and problem-solving challenges, you’ll refine your skills in Unity and game design principles. This course is perfect for intermediate game developers who are familiar with Unity and want to level up their game design skills. There are no strict prerequisites, but prior experience with Unity and C# programming will help you get the most out of this course. The course is designed to help you build scalable, maintainable, and optimized games while providing you with practical tools to solve real-world development challenges. By the end of the course, you will be able to apply design patterns to improve your game’s architecture, optimize performance, create reusable systems, and streamline development processes using Unity 6.
Arizona State University
Putting it All Together: Problem-Solve Like an Entrepreneur
Once you've learned about innovation, caring, and curiosity, you'll need to integrate them as you begin your journey as a technology innovator. You will be asked to articulate your idea using design thinking and learnings to craft an Evidence-Based Pitch Deck.
Universidad Nacional de Colombia
Programación con Python, nivel básico
Este curso introductorio de programación en Python está dirigido a estudiantes universitarios de primeros semestres, estudiantes de secundaria y profesionales que deseen adquirir una base sólida en el desarrollo de software. A través de seis módulos progresivos, se enseñarán los fundamentos de la programación, desde los conceptos básicos hasta la resolución de problemas reales mediante algoritmos y estructuras de control. Al finalizar el curso, los participantes estarán en capacidad de comprender y aplicar los principios esenciales de la programación con Python. Se desarrollarán competencias clave como el diseño de algoritmos, el uso adecuado de estructuras de control (condicionales y ciclos), la creación de funciones reutilizables y la depuración de código. Además, podrán estructurar programas de forma lógica, utilizar librerías especializadas y aplicar herramientas fundamentales del lenguaje. Este curso no solo enseña a programar, sino a pensar con precisión y lógica. Gracias a su enfoque práctico y gradual, constituye una experiencia formativa integral que permite adquirir habilidades técnicas y resolver problemas computacionales de manera eficaz, preparando a los estudiantes para futuros retos académicos y profesionales en el ámbito tecnológico.
LearnQuest
Neural Networks and Random Forests
In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We’ll start with a deep dive into neural networks, building our knowledge from the ground up by examining the structure and properties. Then we’ll code some simple neural network models and learn to avoid overfitting, regularization, and other hyper-parameter tricks. After a project predicting likelihood of heart disease given health characteristics, we’ll move to random forests. We’ll describe the differences between the two techniques and explore their differing origins in detail. Finally, we’ll complete a project predicting similarity between health patients using random forests.
EDUCBA
TIBCO BW Integration: Design, Implement & Test
By completing this course, learners will gain the ability to configure shared resources, implement FTP file transfers, design JMS-to-database workflows, and test integration processes in TIBCO BusinessWorks. They will develop skills to create reusable connections, apply schema-driven data formats, update relational databases, and validate end-to-end integrations with robust error handling. This project-based course provides hands-on practice with real-world scenarios like file transfers between demand systems and HEB databases. Unlike generic tutorials, it focuses on a complete grocery store integration case study, helping learners apply TIBCO BW concepts in a practical, industry-relevant context. Participants will also explore structured testing techniques with Timer activities, ensuring their processes are reliable and production-ready. By the end of the course, learners will be able to design, implement, and test scalable integration solutions using TIBCO Designer. This course is ideal for integration developers, architects, and IT professionals who want to enhance their expertise in enterprise-level integration workflows.
Google
Foundations of User Experience (UX) Design
Foundations of User Experience (UX) Design is the first of a series of seven courses that will equip you with the skills needed to apply to entry-level jobs in user experience design. UX designers focus on the interactions that people have with products like websites, mobile apps, and physical objects. UX designers make those everyday interactions usable, enjoyable, and accessible. The role of an entry-level UX designer might include empathizing with users, defining their pain points, coming up with ideas for design solutions, creating wireframes, prototypes, and mockups, and testing designs to get feedback. Current UX designers and researchers at Google will serve as your instructors, and you will complete hands-on activities that simulate real-world UX design scenarios. Learners who complete the courses in this certificate program should be equipped to apply for entry-level jobs as UX designers. No previous experience is necessary. By the end of this course, you will be able to: - Define the field of UX and explain why it’s important for consumers and businesses. - Understand foundational concepts in UX design, such as user-centered design, the design thinking framework, accessibility, and equity-focused design. - Identify the factors that contribute to great user experience design. - Review common job responsibilities of entry-level UX designers and teams that they work with. - Explore job opportunities and career paths within the field of user experience. - Explain why design sprints are an important and useful part of a UX designer’s work. - Describe common UX research methods. - Identify and account for biases in UX research.
Google Cloud
Responsible AI for Developers: Interpretability & Transparency - 日本語版
このコースでは、AI の解釈可能性と透明性のコンセプトを紹介します。デベロッパーとエンジニアにとって AI の透明性が重要であることについて説明します。データと AI モデルの両方で解釈可能性と透明性を達成できる実践的な方法とツールを検証します。
University of Maryland, College Park
Transforming with Data Analytics and Organization
Every modern organization is a digital organization or will rapidly become digital. Artificial intelligence, Google/Amazon/Facebook/Uber, and big data have dramatically raised customer expectations and demand. Organizations that are effective in using data will win in the economies of the mid-21st century. These must-have core competencies include data analysis, machine learning, data visualizations, data mining, and predictive analytics, and deep learning. Organizations that won't or can't digitally transform will go the way of Blockbuster or Border's Bookstore. The organization that better harnesses the power of data to create a superior customer experience will thrive in the new business realities. The question is, how does an organization digitally transform? There are many digital technologies for organizations to choose from - too many choices! And digital technologies are only part of creating a digital organization. The employees must be trained in the new technologies, leaders must learn how to use data in making strategic decisions, and the organization's business processes must be reinvented. So many choices to make and the stakes have never been higher! This course will give you a framework to help you successfully navigate the challenges posed by digital transformation. First, we will discuss how to use the organization's dynamic capabilities to start the digital transformation. Second, we will use fitness landscapes to build a competitive digital business model. Finally, we will implement a strategic foresight function to help evolve the digital business model for the organization's continued success.
Johns Hopkins University
Data Literacy Capstone – Evaluating Research
This is the final course in the Data Literacy Specialization. In this capstone course, you'll apply the skills and knowledge you have acquired in the specialization to the critical evaluation of an original quantitative analysis. The project will first require you to identify and read a piece of high-quality, original, quantitative research on a topic of your choosing. You’ll then interpret and evaluate the findings as well as the methodological approach. As part of the project, you’ll also review other students’ submissions. By the end of the project, you should be empowered to be a critical consumer and user of quantitative research.
University of Glasgow
Data-Driven Leadership Skills Capstone Project
This course is a capstone assignment requiring you to apply the knowledge and skills you have learned throughout the specialization. In this course, you will choose one of the areas and complete the assignment to pass.
EDUCBA
DirectX 11: Design, Implement & Optimize
Learning outcomes: Design a Windows/DirectX app lifecycle; configure devices, contexts, and swap chains; implement shaders and the graphics pipeline; render frames with clean event loops; handle input and window resizing; optimize presentation with flip-model swaps; and debug, refactor, and finalize a leak-free build. This beginner-friendly course guides learners from “nothing on screen” to a stable, interactive Direct3D 11 application. You’ll set up a runnable pipeline, bind render targets and viewports, and validate with a Hello Direct3D frame before advancing to drawing, texturing, and frame presentation. Along the way, you’ll integrate Win32 input, structure Update/Render/Present for responsiveness, and build a simple star-field demo to practice per-frame updates. Final modules focus on production readiness: resize-safe swap chain management, input/vertex layouts, class-based architecture, and disciplined COM resource cleanup. What makes this course unique is its end-to-end, code-first path that balances fundamentals with real-world details—like choosing formats, using flip-sequential presentation, and organizing rendering code for maintainability. By the end, learners confidently deploy a clear, well-structured DirectX app and know how to extend it.
Google Cloud
Gemini for Security Engineers - 日本語版
このコースでは、Google Cloud の生成 AI を活用したコラボレーターである Gemini が、クラウド環境とリソースを安全に保つうえでどのように役立つかを学習します。サンプル ワークロードを Google Cloud の環境にデプロイする方法、Gemini を使用してセキュリティ構成ミスを特定、修正する方法を学びます。ハンズオンラボでは、Gemini を使用することでクラウドのセキュリティ ポスチャーがどのように向上するかを体験します。 Duet AI は、次世代モデルである Gemini に名称変更されました。
O.P. Jindal Global University
Prescriptive Analytics
This course focuses on enhancing decision-making abilities through mathematical modeling and simulation. Learners will explore how to structure and solve complex business problems using logical thinking and analytical tools, transforming how decisions are approached in real-world contexts. The course introduces a range of optimization techniques, including linear, non-linear, and integer programming, as well as forecasting and basic machine learning methods, to develop effective prescriptive models. Through extensive hands-on practice using Excel, participants will work with real-world datasets across functions such as operations, supply chain, marketing, human resources, and finance. Each module integrates practical case studies, enabling learners to identify decision variables, gather relevant data, model the problem, and evaluate solutions using sensitivity analysis. Emphasis is placed on interpreting model outcomes, collaborating with stakeholders, and effectively communicating results for implementation. In addition to technical modeling skills, the course fosters soft skills like problem framing, teamwork, and engagement with decision-makers. Designed for learners with prior experience in business analytics and Excel, the course is ideal for those seeking to apply data-driven strategies in managerial or data science roles. By the end of the course, learners will be equipped to apply prescriptive analytics for impactful, actionable business decisions.
Dartmouth College
Decision-Making: Blending Art & Science
Why do smart people sometimes think they are right when they are very, very wrong? Our brains are designed to make quick decisions, and sometimes we miss out on what’s really going on. Knowing this, Professor Sydney Finkelstein walks you through the neuroscience behind decision-making, and teaches you to make conscious decisions that are right for you at work and in life. By teaching you to reflect and move forward even better than before, Professor Finkelstein will help you to be the best you possibly can at whatever you do.
Coursera
Validating and Safeguarding Production AI
This long course focuses on the operational lifecycle of agentic AI systems: robust partitioning and dataset management, automated retraining pipelines, continuous monitoring for drift and anomalies, testing and secure deployment, and performance optimization of code and pipelines. You will practice partitioning strategies (time-series and stratified), monitoring and drift detection metrics (PSI and KS), and build CI/CD notebooks and automated workflows for model retraining and re-deployment using tools like MLflow and GitHub Actions. The course addresses software-engineering best practices—clean code, profiling, unit and integration testing—and dependency risk assessment to maintain secure, reliable production systems. Practical assignments include building monitoring alerting rules, implementing retraining triggers, diagnosing runtime bottlenecks, and integrating human-in-the-loop feedback systems to continuously improve models in production while ensuring high code quality and security hygiene.
Coursera
Analyze and Respond to Customer Sentiment
Did you know that over 90% of consumers say how a company responds to feedback directly impacts their loyalty? Understanding and acting on customer sentiment is no longer optional—it is a competitive advantage. This Short Course was created to help digital marketing professionals systematically manage customer interactions across digital channels while leveraging sentiment analysis to drive data-informed engagement strategies and improve customer relationship outcomes. By completing this course, you will be able to analyze customer sentiment data, uncover actionable insights, and apply structured response procedures within CRM systems—skills that help strengthen relationships, boost satisfaction, and refine your engagement strategies. By the end of this 3-hour long course, you will be able to: Apply standard procedures to respond to customer comments and document interactions in a CRM. Analyze weekly sentiment data to derive key customer insights. This course is unique because it combines customer service best practices with data analytics, empowering you to turn customer feedback into measurable improvements and align engagement tactics with real-time sentiment trends. To be successful in this project, you should have: Basic social media knowledge Familiarity with CRM concepts Understanding of customer service principles Data analysis fundamental