The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Coursera
Analyze Sales Data with LibreOffice Base Queries
By the end of this project, you will have developed LibreOffice Base queries that provide data for use in sales analysis. An organization that sells products or services finds it useful to know which products are selling, whether they are priced appropriately, and which customers are purchasing them. Providing that kind of data gives the organization better targets for fine tuning its product mix and customer base. 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
Evaluate, Analyze, and Model Performance
In real-world machine learning work, building a model is only half the job. Knowing how to evaluate it, explain its weaknesses, and defend improvements is what makes your work trustworthy. In this course, you will learn how to evaluate regression and classification models using the right metrics, diagnose where models systematically fail, and determine whether performance differences actually matter. You will practice selecting RMSE and MAE for reporting housing-price models, analyzing confusion matrices to uncover false-positive patterns in spam filters, and using bootstrapping to test whether AUC improvements are statistically significant. Through short videos, guided coaching conversations, hands-on activities, and an ungraded lab, you will build confidence in interpreting model performance the way it is done on real teams. By the end of the course, you will be able to justify your evaluation choices and make evidence-based model decisions.
Google Cloud
APIs Explorer: App Engine
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will get hands-on practice configuring and deploying an App Engine instance with the APIs Explorer tool.
Duke University
Interpretable Machine Learning
As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and trustworthy. This course is a comprehensive, hands-on guide to Interpretable Machine Learning, empowering you to develop AI solutions that are aligned with responsible AI principles. You will also gain an understanding of the emerging field of Mechanistic Interpretability and its use in understanding large language models. Through discussions, case studies, programming labs, and real-world examples, you will gain the following skills: 1. Describe interpretable machine learning and differentiate between interpretability and explainability. 2. Explain and implement regression models in Python. 3. Demonstrate knowledge of generalized models in Python. 4. Explain and implement decision trees in Python. 5. Demonstrate knowledge of decision rules in Python. 6. Define and explain neural network interpretable model approaches, including prototype-based networks, monotonic networks, and Kolmogorov-Arnold networks. 7. Explain foundational Mechanistic Interpretability concepts, including features and circuits 8. Describe the Superposition Hypothesis 9. Define Representation Learning and be able to analyze current research on scaling Representation Learning to LLMs. This course is ideal for data scientists or machine learning engineers who have a firm grasp of machine learning but have had little exposure to interpretability concepts. By mastering Interpretable Machine Learning approaches, you'll be equipped to create AI solutions that are not only powerful but also ethical and trustworthy, solving critical challenges in domains like healthcare, finance, and criminal justice. To succeed in this course, you should have an intermediate understanding of machine learning concepts like supervised learning and neural networks.
Google
Début du processus de conception UX : Empathie, définition et formulation d’idées
Début du processus de conception UX : Empathie, définition et formulation d’idées est le deuxième cours de cette formation certifiante qui vous dotera des compétences nécessaires pour postuler à des emplois de Concepteur UX débutant. Dans le cours 2, vous terminerez les premières étapes du processus de conception d'un projet que vous pourrez inclure dans votre portfolio. Vous apprendrez à faire preuve d’empathie avec les utilisateurs et à comprendre leurs difficultés, à définir les besoins des utilisateurs à l’aide d’énoncés de problèmes et à proposer de nombreuses idées de solutions à ces problèmes. Des concepteurs et chercheurs UX de Google vous serviront d’instructeurs. Vous réaliserez des travaux pratiques simulant des scénarios de conception UX. Les apprenants qui termineront les sept cours de ce programme de formation seront aptes à postuler aux emplois de concepteurs UX débutants. Aucune expérience préalable n’est nécessaire. À la fin de ce cours, vous serez capables de : - Décrire les méthodes de recherche UX courantes. - Faire preuve d’empathie avec les utilisateurs afin de comprendre leurs besoins et leurs difficultés. - Créer des cartes d'empathie, des personnages, des histoires d'utilisateurs et des cartes de parcours utilisateur afin de comprendre les besoins des utilisateurs. - Développer des énoncés de problèmes afin de définir les besoins des utilisateurs. - Générer des idées de solutions possibles aux problèmes des utilisateurs. - Mener des audits concurrentiels. - Identifier et tenir compte des préjugés dans la recherche UX. - Commencer à concevoir une application mobile, un nouveau projet à inclure dans votre portfolio UX professionnel.
University of Michigan
Problem Solving Using Computational Thinking
Have you ever heard that computers "think"? Believe it or not, computers really do not think. Instead, they do exactly what we tell them to do. Programming is, "telling the computer what to do and how to do it." Before you can think about programming a computer, you need to work out exactly what it is you want to tell the computer to do. Thinking through problems this way is Computational Thinking. Computational Thinking allows us to take complex problems, understand what the problem is, and develop solutions. We can present these solutions in a way that both computers and people can understand. The course includes an introduction to computational thinking and a broad definition of each concept, a series of real-world cases that illustrate how computational thinking can be used to solve complex problems, and a student project that asks you to apply what they are learning about Computational Thinking in a real-world situation. This project will be completed in stages (and milestones) and will also include a final disaster response plan you'll share with other learners like you. This course is designed for anyone who is just beginning programming, is thinking about programming or simply wants to understand a new way of thinking about problems critically. No prior programming is needed. The examples in this course may feel particularly relevant to a High School audience and were designed to be understandable by anyone. You will learn: -To define Computational Thinking components including abstraction, problem identification, decomposition, pattern recognition, algorithms, and evaluating solutions -To recognize Computational Thinking concepts in practice through a series of real-world case examples -To develop solutions through the application of Computational Thinking concepts to real world problems
Whizlabs
Modeling in AWS
Modeling in AWS is the third course in the AWS Certified Machine Learning Specialty specialization. The major focus of this course is to train Machine learning Models by analyzing Modeling concepts in AWS. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 1:30 Hours- 2:00 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners. Module 1: Modeling and Training Machine Learning Models in AWS Module 2: Machine Learning Models: Performance evaluation and Tuning By the end of this course, Learners will be able to : 1. Analyze Modeling Concepts and train Machine Learning Models 2. Examine performance of machine learning models 3. Implement automatic model tuning by training a model
Google Cloud
運用 BigQuery 建立嵌入項目、向量搜尋和 RAG
This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.
University of California, Davis
SQL for Data Science
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems. This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes. You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL. It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables. You'll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling. You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!
EDUCBA
3DS Max Texturing: Apply, Create & Refine
By the end of this course, learners will be able to apply detailed UV-mapped textures, create lifelike facial and body details, refine clothing surfaces, and design realistic shaders for eyes and materials in 3ds Max. This course takes students step-by-step through the professional workflow of texturing characters in 3ds Max using Photoshop and UV unwrapping. Starting with the head, lips, and eyebrows, learners gain hands-on experience in painting and aligning textures for natural skin tones and expressive facial features. The journey continues with body, hands, and clothing, where learners explore how to craft fabric details, refine jacket seams, and add subtle realism through burn and shading techniques. Finally, learners will master the use of shaders, enhancing eyeballs with glossiness and reflection to achieve cinematic realism. What makes this course unique is its practical, project-based approach—focused on Shrek-style character modeling—that bridges technical precision with creative artistry. Upon completion, learners will possess industry-ready skills to texture, shade, and polish 3D characters, making them production-ready for animation, games, or film projects.
Rice University
Physics 101 - Energy and Momentum
This second course serves as an introduction to the physics of mechanical energy and momentum. Upon completion, learners will understand how mathematical laws and conservation principles describe the motions and interactions of objects around us. Learners will gain experience in solving physics problems with tools such as graphical analysis, algebra, vector analysis, and calculus. This first course covers Energy, Translational Momentum, Collisions, Statics, and Elasticity. Each of the three modules contains reading links to a free textbook, complete video lectures, conceptual quizzes, and a set of homework problems. Once the modules are completed, the course ends with an exam. This comprehensive course is similar in detail and rigor to those taught on-campus at Rice. It will thoroughly prepare learners for their upcoming introductory physics courses or more advanced courses in physics.
Google
Activos, amenazas y vulnerabilidades
En este quinto curso del Certificado de Ciberseguridad de Google, explorarás los conceptos de activos, amenazas y vulnerabilidades. Primero conocerás cómo se clasifican los activos. Luego, te profundizarás sobre las amenazas y vulnerabilidades más comunes, así como los controles de seguridad que utilizan las organizaciones para proteger la información valiosa y mitigar el riesgo. Además, practicarás el proceso de modelado de amenazas y desarrollarás una mentalidad de atacante. También, aprenderás tácticas para anticiparte a los riesgos de seguridad. Te guiarán especialistas de Google, que actualmente trabajan en ciberseguridad, con actividades prácticas y ejemplos que simulan tareas comunes y frecuentes de este campo. Todo esto te ayudará a desarrollar tus habilidades y prepararte para trabajar. Los/las estudiantes que completen este certificado estarán preparados/as para solicitar trabajo en el área de la ciberseguridad, en un nivel inicial. No se necesita experiencia previa.
Universidad Austral
La enseñanza de las Ciencias Naturales en la escuela primaria
Los científicos y las científicas son “aprendices profesionales”: se dedican a formular preguntas, encontrar observaciones discordantes, poner en duda aquello que no cierra y construir nuevas respuestas que permitan entender mejor el mundo en que vivimos. En este curso, desarrollarás las estrategias necesarias para lograr que tus estudiantes aprendan no sólo conocimientos científicos conceptuales sino también aquellas herramientas que les permitan investigar el mundo que los rodea, de modo similar a como hacen los científicos y científicas. El curso es accesible tanto para aquellos que están dando sus primeros pasos en enseñanza de las ciencias como para quienes ya cuentan con experiencia o formación en el tema; no se necesita ningún laboratorio o material complejo. Conversaremos acerca de la naturaleza de la ciencia, compartiremos estrategias para promover un rol activo de los estudiantes en la construcción del conocimiento, y trabajaremos la evaluación y la metacognición al servicio del aprendizaje. Al finalizar, habrás conocido los principales ejes de conversación contemporáneos acerca de la enseñanza de las ciencias naturales en el marco de las llamadas habilidades del siglo XXI, y desarrollado herramientas concretas para antes, durante y después de la clase. Este curso fue diseñado por la Fundación Bunge y Born en alianza con la Fundación Perez Companc, en el marco del Programa Sembrador.
SkillUp
Currency Transaction Reports - US
Currency Transaction Reports (CTRs) are a cornerstone of anti-money laundering compliance and a critical regulatory obligation for financial institutions. This course provides a clear, practical overview of CTR requirements under the Bank Secrecy Act, with a strong focus on accurate reporting, documentation, and regulatory readiness. You will learn how to identify reportable cash transactions, apply the $10,000 reporting threshold, and correctly aggregate multiple transactions conducted in a single business day. The course also explains essential recordkeeping requirements and retention timelines, helping you maintain documentation that withstands regulatory audits and examinations. Additionally, you will develop practical skills to recognize common structuring patterns, such as amount structuring, location structuring, and third-party structuring, that indicate attempts to evade CTR filing. Through realistic scenarios and guided practice, you’ll learn how to make sound compliance decisions and support your institution’s AML efforts. Designed for frontline staff and compliance professionals, this course builds the confidence and judgment needed to execute CTR responsibilities accurately and consistently.
Coursera
Create an Affinity Diagram Using Creately
By the end of this project you will create an affinity diagram using Creately.com. Learning to collect and organize ideas and information increases productivity and fosters positive teamwork. Learners will engage in the Affinity process to develop an understanding of how to spark, gather, consolidate, sort and present ideas and information.
Coursera
Comment faire de la pubicité sur Pinterest
Dans ce projet guidé d'une heure. vous apprendrez comment créer un compte professionnel sur Pinterest, faire de la publicité et savoir comment réussir sur Pinterest. À la fin de ce projet, vous aurez appris à faire de la publicité sur Pinterest.