The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Coursera
Google Bard for Beginners: Text Generation with Prompts
In this 1-hour project-based course, you'll dive into text generation using Google Bard, MakerSuite, and the PaLM API on Google Colab. We'll start with an exploration of PaLM's integration with Bard and MakerSuite, followed by interactive sessions with Bard to explore various prompt themes, and hands-on experimentation with text and chat prompts in MakerSuite. As you progress, you'll get hands-on experience with different facets of text generation, exploring the capabilities of each tool, and understanding their unique features. This project is designed to provide a practical understanding of generative AI tools and how they can be utilized for various text generation tasks. With no stringent prerequisites, this course is accessible for a broad audience, offering a step-by-step approach to exploring and creating with generative AI, leaving you with valuable insights and a comprehensive project showcasing the skills acquired.
Skillshare
How to Draw: A Beginner’s Guide Pt 3 – Drawing in Practice
*PLEASE NOTE* This Specialization will be deprecated and removed from Coursera on April 5, 2026 In the final part of this foundational series, you’ll put your skills to the test with real-time drawing demos led by Brent Eviston. Watch as Brent brings birds and botanicals to life in two extended, start-to-finish projects. Along the way, you’ll reinforce everything you’ve learned—composition, shape, structure, line, and value—while gaining new insights into the drawing process in action. You’ll also get practical tips for organizing your materials and setting up your workspace to support creative flow and comfort. Whether you draw alongside the demos or observe and reflect, this course is designed to help you transition from learning to doing. You’ll come away with: - A clear view of the full drawing process from start to finish - Deeper understanding of real-time decision making - More confidence applying your skills to complex subjects - A solid studio setup to support your creative practice It’s the perfect capstone to your beginner drawing journey—and a launching point into more advanced practice. Instructor bio: Brent Eviston is an artist and educator whose passion for teaching is matched only by his love of drawing. He is the creator of the award-winning online series The Art & Science of Drawing, which has enrolled more than half a million students across 180+ countries. With over 20 years of experience teaching in art studios, schools, and museums, Brent has developed highly effective methods for helping students see the world differently through drawing. His own practice spans traditional figure drawing, architectural and anatomical studies, as well as contemporary explorations.
Coursera
Verify Jira History: Confirm Accuracy Fast
Imagine this: a critical task for your project’s upcoming release is marked as "In Review." Based on this status, your project manager confidently reports to stakeholders that the feature is on track. But the developer assigned to it is actually blocked, waiting for information from another team. They left a vague comment about it a week ago, but no one saw it. The ticket’s status is a lie. Now, with the deadline looming, a frantic scramble begins. Trust is broken, schedules are thrown into chaos, and the team is forced into reactive firefighting mode, all because your project's "single source of truth" was wrong. This scenario is not an exception; it is a daily reality in countless organizations. The promise of a tool like Jira is clarity and alignment, but that promise is broken the moment the data within it becomes unreliable. When issue histories are a tangled mess of rapid status changes, when comments are vague or contradictory, and when the official status doesn't match the real-world situation, your project’s foundation turns into a house of cards. Every report becomes suspect, every planning session is based on guesswork, and every team member is at risk of working on the wrong thing at the wrong time. It’s time to stop trusting and start verifying. Verify Jira History: Confirm Accuracy Fast is a focused, hands-on course designed for any professional—Project Manager, QA Engineer, Scrum Master, Developer, or Team Lead—who depends on the integrity of their project data. This course moves beyond basic issue tracking and teaches you the critical and often-overlooked skill of forensic analysis. You will learn to be the detective for your project, methodically investigating a Jira issue to ensure its status is an undeniable reflection of its real-world progress. This is not a course about how to use Jira’s basic features. This is a course about how to master the truth-finding tools that lie just beneath the surface. You will learn a systematic, repeatable process to analyze an issue's complete lifecycle, interpret the human context hidden in its comments, and cross-reference your findings to confirm that what Jira says is what is actually happening. Our journey is a deep dive into the three layers of an issue’s story: 1. The Unimpeachable Log: Analyzing the Change History First, you will learn to read an issue’s history tab not as a boring log, but as the unimpeachable paper trail of its journey. This is where the raw data lives, free of opinion or misinterpretation. Through expert demonstrations and practical checklists, you will learn to spot critical patterns and red flags. You’ll become adept at answering key questions by analyzing changes to core fields: - Status Changes: Does the issue flip-flop between "In Progress" and "To Do"? This could signal a blocker or constant reprioritization. - Assignee Changes: Was the ticket passed around between multiple people like a hot potato? This often indicates confusion about ownership. - Field Updates: Were story points changed late in the sprint? Was the due date pushed out multiple times? These are clues about scope creep and estimation accuracy. 2. The Human Story: Interpreting Comments for Hidden Context Next, you will master the art of comment analysis. The history log tells you what happened, but the comments tell you why. This is where the human element—the context, the confusion, the collaboration—is found. You will learn to move beyond passively reading comments and start actively interpreting them. We will teach you to identify: - Keywords and Phrases: Learn to scan for critical terms like "blocked," "waiting for," "need more info," or "dependency," which instantly signal that an issue's "In Progress" status might be misleading. - The Narrative Flow: Is there a clear conversation happening, or is it a series of disconnected statements? You'll learn to follow the thread of a discussion to understand how a decision was reached. - Ambiguity vs. Clarity: You will learn to recognize the difference between a helpful comment ("@John Smith, the API key you provided is returning a 403 error. Can you please grant permissions?") and an unhelpful one ("It’s not working."). 3. The Final Verdict: Cross-Referencing to Confirm the Truth In the final section, you will learn to bring all the evidence together to make a definitive judgment. This is where your forensic skills culminate in confirmation. You’ll learn to cross-reference your findings by checking: - Linked Issues and Dependencies: Does the status of this ticket align with the status of the tickets it's blocking or is blocked by? - Source Code Commits and Pull Requests: Do the linked developer branches and pull requests actually contain code related to this issue, and what is their status? - Attached Files and Documentation: Do the attachments (like mockups or logs) support the work described and its current state? Through hands-on analysis of realistic, "messy" Jira tickets, you will practice this entire workflow. By the end of this course, you will no longer be a passive consumer of project data; you will be an active guardian of its integrity. You will have the skills and confidence to validate any Jira issue, challenge its status when necessary, and guide your team toward a culture of clarity and accountability. Your project documentation will become reliable, your team’s collaboration will be more seamless, and your project's integrity will never be in question, because you will know how to find the truth.
Banco Interamericano de Desarrollo
Gobierno Digital
En este curso aprenderás qué es el gobierno digital, por qué es importante y cómo se puede promover. A través de los distintos contenidos podrás analizar cómo la transformación digital de gobierno afecta a los ciudadanos en su día a día y podrás entender algunos de los aspectos más importantes del gobierno digital como lo son la identidad y firma digital, datos, interoperabilidad, servicios digitales y ciberseguridad. El curso te brindará todas las herramientas que necesitas para empezar a aportar en la transformación digital de tu gobierno, por lo que no es necesario contar con conocimientos previos sobre tecnología. Si obtienes el certificado final del curso, también recibirás una insignia digital que te permitirá compartir fácilamente y de forma más confiable las habilidades o el conocimiento adquirido con tu red profesional. Este curso es parte de la Especialización en transformación digital de Gobiernos, la cual te dará una mirada más amplia para la implementación de la digitalización en los procesos, trámites y gestiones para un mejor servicio a la ciudadanía.
Amazon
Generative AI in Software Development
In this course, you'll explore Generative AI's role in software development. You'll start with an overview to understand its capabilities. Next, you'll dive into specific tools like Amazon CodeWhisperer, where you'll learn to automate tasks such as code completion and bug detection. By the end, you'll evaluate Generative AI's benefits and limitations. This will empower you to make informed decisions about its use in software development. After completing this course, you’ll be able to: • Discuss the principles and applications of Generative AI. • Implement Generative AI tools in software development. • Examine the role of Generative AI in automating repetitive tasks in software development. • Evaluate the benefits and limitations of using Generative AI in software development.
EDUCBA
Master AI & AWS Cloud Skills: Analyze, Build, Deploy
Learners will be able to explain core AI concepts, differentiate machine learning techniques, analyze AWS AI services, apply model training workflows, and evaluate end-to-end AI solutions using real-world examples. This course equips participants with a complete understanding of Artificial Intelligence fundamentals while developing practical cloud skills using AWS tools such as SageMaker, Comprehend, Rekognition, Lex, and Polly. Through clear video-based instruction and structured module progression, learners gain the ability to design conversational agents, build computer vision pipelines, prepare datasets, train and optimize ML models, implement foundation models, and deploy intelligent cloud applications. By completing hands-on demonstrations and graded assessments, learners strengthen their technical confidence and prepare for the AWS Certified AI Practitioner exam. What makes this course unique is its step-by-step learning path, AWS-focused practical guidance, and real-world case studies that connect AI theory with cloud implementation. The course blends foundational knowledge with applied AWS workflows, making it ideal for beginners, aspiring cloud practitioners, and professionals seeking to expand their AI and ML capabilities.
American Museum of Natural History
Evolution: A Course for Educators
How are all of the species living on Earth today related? How does understanding evolutionary science contribute to our well-being? In this course, participants will learn about evolutionary relationships, population genetics, and natural and artificial selection. Participants will explore evolutionary science and learn how to integrate it into their classrooms.
KodeKloud
Introduction to OpenAI
Welcome to the Introduction to OpenAI Course, your gateway into the world of artificial intelligence and advanced language models. In today’s fast-paced AI environment, understanding the foundational elements of AI is essential. However, the true value lies in knowing how to effectively use OpenAI’s tools and frameworks to create meaningful, transformative AI applications. If you’ve ever felt uncertain about working with complex AI models, you're in the right place. While many introductory tutorials offer only a basic overview, this course goes further by guiding you through real-world OpenAI applications with depth and clarity. Designed for learners who are ready to bridge the gap between theoretical AI concepts and practical implementations using OpenAI’s platform, this course offers hands-on, scenario-based lessons. Through these lessons, you’ll build the skills to confidently work with OpenAI tools, advancing beyond the basics and gaining valuable, applicable insights into AI modeling. The course is divided into several modules to ensure a comprehensive learning experience. The first module, Pre-requisites, sets the stage with essential foundational steps, such as an introduction to OpenAI, account setup, an overview of OpenAI’s platform, securing API keys, understanding OpenAI’s model options, and navigating key libraries and changelogs. This module ensures you have a strong start and the necessary tools for success. In Introduction to AI, you will dive into the evolution of AI, from rule-based systems to deep learning, and discover how transformers and attention mechanisms power today’s generative AI models. You’ll also cover important topics such as prompt engineering, tokenization, pre-training, AI ethics, multimodal inputs, reinforcement learning, and key considerations for responsible AI solutions. The Text Generation module focuses on the ins and outs of text generation, including prompt engineering and practical applications. Hands-on labs and projects will guide you through creating text-based solutions like recipe generators, article translators, and short story generators. You’ll also explore OpenAI’s tools for sentiment analysis, fine-tuning, text-to-speech, and embeddings, with projects that include developing an AI research assistant and a personalized AI trainer. In the Features module, you’ll gain expertise in structured outputs, function calling, and batch processing with OpenAI, and explore advanced usage techniques and content moderation. Hands-on labs will help you manage and scale AI solutions effectively. Finally, the Vision module introduces you to OpenAI’s cutting-edge vision capabilities with DALL-E and CLIP. You’ll gain an overview of DALL-E's text-to-image generation and explore its evolution and applications across various industries. Projects in this module will include image generation, captioning, and fine-tuning techniques. You’ll also discuss ethical considerations, current limitations, and future innovations, gaining insight into the transformative potential of AI-driven vision technologies. Through this hands-on, project-based course, you’ll develop a robust understanding of OpenAI’s language and vision models, enabling you to build innovative applications. Whether you’re looking to deepen your knowledge of AI or apply it to real-world challenges, this course equips you with the tools to excel in OpenAI’s ecosystem and beyond.
Universidad de los Andes
Los portafolios y las inversiones en el mercado de capitales
En la medida en que las personas o las entidades requieren invertir sus posiciones de liquidez en el mercado de capitales se hace necesario estudiar los activos financieros y entender el funcionamiento del mercado de valores para tomar decisiones informadas y sustentadas que permitan a los inversionistas decidir adecuadamente los niveles de riesgo-retorno que se desea tomar. Este curso aborda la idea principal de la diversificación vía la conformación de portafolio de inversión con el objetivo de maximizar la rentabilidad minimizando el riesgo. El curso igualmente introduce los modelos básicos de inversión de largo plazo basados en la teoría de la eficiencia del mercado. El curso presenta una evolución conceptual de los elementos más básicos del entendimiento del mercado de capitales, hasta las estrategias de formación y análisis de portafolios eficientes. Al final del curso los participantes tendrán una visión general de los principales modelos y herramientas para invertir en portafolio de activos financieros. Este curso está pensado para personas de diferentes disciplinas que quieren entender y profundizar en las estrategias básicas para invertir en el mercado de capitales con un enfoque de largo plazo. El curso de concentra en los conceptos básicos de la conformación y análisis de la riesgo - rentabilidad de los portafolios de inversión en el mercado de capitales.
Copenhagen Business School
Social Business Model and Planning for Social Innovation
In this course we will take the social business opportunity that you have identified in the first course to a higher level. Specifically, you will develop a business model using the Business Model Canvas. Gradually you will also start writing your business plan. Moreover, you will be able to assess different organizational forms and select the one that is appropriate for your developed business model. By the end of the course you will be able to compare different social impact investment methods and choose the right funding strategy for your social venture. Note: It is highly recommended to have completed Course 1: 'Identifying Social Entrepreneurship Opportunities' before you start with this Course!
Arizona State University
Selective Laser Sintering and Metal Laser Powder Bed Fusion
Powder bed fusion is one of the additive manufacturing processes that has found the most application in functional part production. In this course we discuss this process in the context of polymers (selective laser sintering) and metals (laser powder bed fusion), with an emphasis on machine setup and post-processing. The necessary elements for each course are lecture videos, knowledge checks, and project completion. For additional information on certain topics, I've included supplemental readings and videos throughout various lessons that might enhance your knowledge. Because all resources are not available to all students, these materials are purely optional. In addition, you will note that some of the lectures feature our department’s graduate students. These excellent students are sometimes closer to the material, having learned it recently, so we greatly appreciate their participation in the instructional process.
EDUCBA
Analyze Fatal Drug Overdose Data Using Tableau
By the end of this course, learners will be able to analyze real-world fatal accidental drug overdose data, apply structured data preparation and exploratory analysis techniques, engineer meaningful analytical features, and interpret trends to generate validated, data-driven insights using Tableau. Learners will also develop the ability to communicate findings clearly through a cohesive, end-to-end analytical project. This course provides hands-on experience with a realistic public health dataset, enabling learners to move beyond tool-centric training and focus on analytical thinking, problem framing, and responsible data interpretation. Participants will learn how to clean and explore complex datasets, design effective analytical approaches, validate insights, and translate results into actionable conclusions. What makes this course unique is its end-to-end, project-driven structure centered on a sensitive and impactful real-world use case. Rather than isolated exercises, learners complete a complete analytical workflow that mirrors industry expectations. The course emphasizes ethical awareness, analytical rigor, and storytelling with data, making it especially valuable for aspiring data analysts, BI professionals, and Tableau practitioners seeking practical, portfolio-ready experience grounded in real-world decision-making.
Universidade de São Paulo
Boas Práticas Científicas
Este curso, destinado a doutorandos, pós-doutorandos, pesquisadores e professores universitários envolvidos em pesquisa científica, aborda as Boas Práticas Científicas. Alunos de mestrado e iniciação científica também poderão aproveitar a maior parte de seu conteúdo. A ciência de alta qualidade exige não apenas rigor metodológico, mas também uma sólida base ética. Por isso, oferecemos uma imersão nos conceitos essenciais das Boas Práticas Científicas, abordando criticamente os desafios contemporâneos da pesquisa. Dividido em 4 módulos, o curso cobre Ética em Pesquisa, Integridade Científica, Avaliação de Pesquisa e Relações Interpessoais e Ambiência. Matricule-se no curso e tenha contato com questões essenciais para execução de pesquisa científica com qualidade, responsabilidade e ética.
Packt
Foundations of Oracle Database Administration
Dive into the essential skills needed to become a proficient Oracle Database Administrator with this comprehensive course. You will learn to install, configure, and manage Oracle databases, setting a strong foundation for a career in database administration. Gain hands-on experience with the practical tools and techniques required to maintain secure, high-performing database environments. The course begins with an introduction to relational database management systems (RDBMS) and the Oracle database ecosystem. You'll explore core database architecture, learn to set up a practice environment, and understand the role of a DBA. Through step-by-step guides, you'll master installation processes, database creation, and key administration tasks on Linux and Windows platforms. As you progress, you'll delve into advanced topics, including database initialization, data dictionary queries, and multitenant architecture. Hands-on practice will solidify your skills, enabling you to administer both container and pluggable databases effectively. Real-world scenarios and documentation usage will prepare you for professional challenges. Ideal for aspiring and practicing DBAs, this course caters to learners with basic IT knowledge. With its beginner-friendly approach and hands-on labs, you'll gain confidence to advance in the competitive field of database administration.
Microsoft
Microsoft Fabric: Data Governance, Security, and Analytics
In this course, you will focus on implementing data governance, security controls, and real-time analytics capabilities in Microsoft Fabric. You will set up Microsoft Purview for data cataloging and lineage, configure security with Microsoft Entra ID, and develop event-driven data solutions. The course also covers compliance readiness, monitoring, and advanced data mirroring techniques, providing hands-on experience with EventStreams, Data Activator, and Azure Stream Analytics. By the end of the course, you will have a comprehensive toolkit for building secure, compliant, and responsive data platforms.
DeepLearning.AI
Build Better Generative Adversarial Networks (GANs)
In this course, you will: - Assess the challenges of evaluating GANs and compare different generative models - Use the Fréchet Inception Distance (FID) method to evaluate the fidelity and diversity of GANs - Identify sources of bias and the ways to detect it in GANs - Learn and implement the techniques associated with the state-of-the-art StyleGANs The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs. This Specialization provides an accessible pathway for all levels of learners looking to break into the GANs space or apply GANs to their own projects, even without prior familiarity with advanced math and machine learning research.