The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
DeepLearning.AI
Structuring Machine Learning Projects
In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.
Stanford University
Game Theory II: Advanced Applications
Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making and voting systems), mechanism design, and auctions. In the first week we consider the problem of aggregating different agents' preferences, discussing voting rules and the challenges faced in collective decision making. We present some of the most important theoretical results in the area: notably, Arrow's Theorem, which proves that there is no "perfect" voting system, and also the Gibbard-Satterthwaite and Muller-Satterthwaite Theorems. We move on to consider the problem of making collective decisions when agents are self interested and can strategically misreport their preferences. We explain "mechanism design" -- a broad framework for designing interactions between self-interested agents -- and give some key theoretical results. Our third week focuses on the problem of designing mechanisms to maximize aggregate happiness across agents, and presents the powerful family of Vickrey-Clarke-Groves mechanisms. The course wraps up with a fourth week that considers the problem of allocating scarce resources among self-interested agents, and that provides an introduction to auction theory. You can find a full syllabus and description of the course here: http://web.stanford.edu/~jacksonm/GTOC-II-Syllabus.html There is also a predecessor course to this one, for those who want to learn or remind themselves of the basic concepts of game theory: https://www.coursera.org/learn/game-theory-1 An intro video can be found here: http://web.stanford.edu/~jacksonm/Game-Theory-2-Intro.mp4
Google Cloud
Managing Security in Google Cloud
This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, Cloud IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.
University of Colorado Boulder
Network Systems Foundations
Welcome! Throughout this course, Network Systems Foundations, you will delve into the fundamental layers of network communication. You will start with a thorough discussion of the Link Layer and its crucial role, moving on to the intricacies of Internet Protocol (IP) and router data planes, and then navigate through the complexities of the transport layer, application layer, and network security. With a practical focus, you'll write Python code to manage routing tables, analyze network traffic, simulate router functionalities, and create digital certificates for web servers. By the end of this course, you will have a well-rounded understanding of networking principles, from data transmission and routing to application protocols and security, and will be equipped with practical skills to navigate the ever-evolving landscape of network technology. By completing this course, learners will be able to: 1. Describe the layers in depth and how they relate to one another 2. Analyze traffic through python programming 3. Design a simplified routing protocol that has similar features as to what powers the Internet 4. Create a client and server with socket programming 5. Generate certificates for TLS which powers the security in https This course can be taken for academic credit as part of CU Boulder’s MS in Electrical Engineering or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Electrical Engineering: https://www.coursera.org/degrees/msee-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder Course logo by Jordan Harrison on Unsplash.
University of Colorado Boulder
Basics of Inclusive Design for Online Education
This course provides instruction and strategies to support you in developing a course that is inclusive to students with a wide range of abilities, including students with disabilities. We cover effective practices to increase inclusion and avoid some of the common accessibility issues that can arise in an online course. In particular, Basics of Inclusive Design Online covers course organization, the accessibility of Microsoft Office and PDF documents, making course instruction pages accessible, captioning of videos, making images accessible, and designing for learning differences. We also discuss how inclusive course materials can help all students, including students without disabilities. This course will appeal to those who want both a broad overview of the range of accessibility considerations and also a step-by-step guide of how to check documents for accessibility, caption a video, or prepare course content for non-visual users. Course logo credit: "web accessibility word cloud" by Jill Wright (https://goo.gl/xyUoeU). Copyright - some rights remain. See https://creativecommons.org/licenses/by/2.0/
EDUCBA
Analyze and Apply Project Finance Methods and Functions
By the end of this course, learners will be able to analyze project finance structures, evaluate project risks and mitigation strategies, interpret pricing mechanisms, and apply financial functions and models to real-world infrastructure projects. This course provides a comprehensive, practice-oriented introduction to project finance methods and functions, with a strong focus on infrastructure and BOT-based projects. Learners will explore the full lifecycle of project finance—from understanding project types and stages to managing risks, structuring repayments, and evaluating pricing decisions. The course also introduces essential financial modeling tools, including date functions, lookup functions, and data analysis techniques commonly used in project finance models. What makes this course unique is its integration of financial concepts with applied modeling techniques, allowing learners to connect theory with hands-on analytical skills. Through structured modules, real-world examples, and assessment-aligned learning activities, learners gain practical insights into how lenders and project sponsors evaluate bankability and financial sustainability. This course is ideal for finance professionals, analysts, infrastructure planners, and learners seeking to build job-ready skills in project finance and financial modeling.
University of Maryland, College Park
Selecting the Right Customer & Channel
In a world where businesses have unprecedented access to customer data, the ability to manage and influence relationships effectively has become essential. This course explores how firms establish and nurture relationships with both Business-to-Consumer (B2C) and Business-to-Business (B2B) customers, while also evaluating the financial implications of these connections. By the end of the course, you will have the skills to analyze customer acquisition costs, evaluate the financial impact of marketing channels, and leverage customer analytics to foster stronger, more cost-effective relationships in the digital marketplace.
Alex Genadinik
Blockchain And Cryptocurrency Definitions For Beginners
This is ideal for people not familiar with the Cryptocurrency world, who want to take their first step to learning about it today. After this course, you will: Understand how the Blockchain technology works at a 10,000 foot level Understand applications of Blockchain beyond just trading Take your first steps in the Cryptocurrency world DON'T MISS THE CRYPTOCURRENCY MARKET Many people take a long time looking for a good industry to get into as the available industries mature and get more competitive. I've observed this with many industries like the SEO industry, Ecommerce, Elearning, and much more. Don't stand on the sidelines planning. Start doing instead. We are already quite a ways into the Cryptocurrency space, but if you look at the big picture, today is still a good time to get into it. WHAT I WISH I HAD KNOWN WHEN STARTING The content in this course is based on what I wish I had a full understanding of early on. When I started in the Cryptocurrency space, I only had half-understanding of many concepts which prevented me from making the best investments I could and making the best decisions I could. So I added those concepts to this course so you don't have to struggle with them. THIS IS A RAPIDLY-EVOLVING SPACE, TELL ME WHAT YOU WANT TO LEARN IN IT In addition to the content in the course that I thought would be good to have, I am the type of instructor who is very open to ideas of students. So if there is something you want to learn about the Cryptocurrency world or something that is confusing you that is not already in the course, please let me know and I'll add it to the course. DISCLAIMER 1: The content in this course is not investment advice, not legal advice, and not accounting advice. DISCLAIMER 2: You will have to sign up for some services shown in the course and some services are paid. I am only showing you industry-standard services and I don't profit from showing them to you. I only show them for educational purposes. Invest in your future! Enroll today!
Google Cloud
Looker Developer - Qwik Start
This is a Google Cloud Self-Paced Lab. In this lab, you will learn about the fundamental LookML structures, create a view, and join the new view to an existing explore.
Coursera
Engaging and Assessing Students with Plickers
By the end of this project, you will have created a Plickers account complete with Plickers assessments, fully equipping you to begin using Plickers with your students right away. Plickers is a free online tool that allows you to instantly check student understanding. Best of all - your students do not need their own devices in order to use Plickers. Plickers allows students to respond with QR codes as you scan the room to check for understanding! During this project, we will work together to set up your Plickers account and learn how to create assessments you can use with your class or at home. We will also learn how to use the data we collect from these assessments in order to inform and adjust our instruction. *You will need a free Plickers account for this project.
Arizona State University
Rapid Prototyping Materials and Tooling
Hello, everyone! Welcome to this course on Rapid Prototyping Materials and Tooling. This is part of the Rapid Prototyping and Tooling specialization. In this course, I’ll cover the characteristics and appropriate uses of a variety of prototyping materials, including cardboard, plastic, wood, and aluminum. I’ll also cover some of the common forms of traditional machining used in making prototypes, as well as more advanced manufacturing tools such as 3D printers, laser cutters, and more! By the end of this course, you should have a better understanding of the strengths and weaknesses of common prototyping materials and manufacturing processes, as well as the situations in which their use is most appropriate. The hope is that by having a better understanding of these materials and machines, you will be able to better develop high-quality prototypes. I’m excited to teach this course as I am really passionate about the content in it. So without further ado, let’s dive into the world of rapid prototyping!
Coursera
Optimize AI: Plan, Evaluate, and Learn
Optimize AI: Plan, Evaluate, and Learn – equips project and program managers with the skills to guide AI systems through change and uncertainty. In this course, you’ll learn how to analyze performance data to plan retraining, evaluate algorithm families under real-world constraints, and design continuous-learning strategies with canary deployments and rollback safeguards. Through scenario-based discussions, hands-on activities, and practical tools like MLflow dashboards, evaluation matrices, and retraining calendars, you’ll practice making informed decisions under pressure. By the end, you’ll be able to detect risks early, balance accuracy and speed, and sustain reliable AI systems that align with business goals.
Coursera
Wireshark for Security: Detect Network Anomalies
Enhance your network security skills using Wireshark to detect and analyze network anomalies. In this intermediate guided project, you’ll explore Wireshark's powerful packet-capturing features to identify suspicious activities and potential cyber threats. In practice, you will learn to capture traffic, save it, and filter out a specific flow based on specific criteria. Gain hands-on experience with real-time traffic analysis, anomaly detection techniques, and basic networking security principles. This project is ideal for network engineers and cybersecurity professionals aiming to bolster their network defense capabilities. The recommended background for this project is a basic understanding of networking concepts, and familiarity with network protocols and traffic flow (e.g. HTTP, TCP, UDP, etc.). By the end, you’ll be proficient in identifying unusual patterns and enhancing your organization’s security posture.
Google Cloud
Modernize Infrastructure and Applications with Google Cloud - Español
Muchas empresas tradicionales usan aplicaciones y sistemas heredados que no pueden adecuarse a las expectativas de los clientes actuales. A menudo los líderes empresariales deben elegir entre mantener sus sistemas de TI anticuados o invertir en nuevos productos y servicios. En “Modernize Infrastructure and Applications with Google Cloud”, se exploran estos desafíos y se ofrecen soluciones para superarlos con la tecnología de la nube. Como parte de la ruta de aprendizaje de Cloud Digital Leader, el objetivo de este curso es ayudar a las personas a crecer en su rol y desarrollar el futuro de su empresa.
Codio
Java: Non-Linear Data Structures
Code and run your first Java program about data structures and algorithms in minutes without installing anything! This course is designed for learners familiar with Java basics and object-oriented programming. It provides a solid foundation of not just Java, but core data structures and algorithms topics that can be transferred to other languages. The modules in this course cover non-linear data structures like heaps, hash tables (and maps), graphs, and sets. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to small, approachable coding exercises that take minutes instead of hours.
Google Cloud
Menggunakan BigQuery Machine Learning untuk Inferensi
Pelajari BigQuery ML untuk Inferensi, mengapa Analis Data harus menggunakannya, kasus penggunaannya, dan model ML yang didukung. Anda juga akan mempelajari cara membuat dan mengelola model ML ini di BigQuery.