The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Google Cloud
運用 Gemini Enterprise 加速知識交流
Gemini Enterprise 結合 Google 的搜尋和 AI 輔助功能，企業員工只要在單一搜尋列輸入關鍵字，就能查找文件儲存空間、電子郵件、對話、支援單處理系統和其他資料來源中的特定資訊。Gemini Enterprise 助理還能協助人員腦力激盪、研究資訊、列出文件大綱及執行其他動作，例如邀請同事加入日曆活動，加快完成知識型工作及各種協作作業。(請注意，Gemini Enterprise 先前稱為 Google Agentspace，本課程可能會提及產品舊稱。)
Coursera
كيفية إنشاء صورة مصغرة لليوتيوب باستخدام كانفا
بنهاية هذا الدورة التدريبية، سوف تقوم بإنشاء حساب مجاني على كانفا، الذي من خلاله ستنشئ صورة مصغرة لتحميها على مقاطع الفيديو التي ستشاركها مع متابعيك اليوتيوب. ستكون قادرًا على دمج مخطط الألوان والصور وعناصر التصميم الأخرى التي ستجذب جمهورك. ستتضمن هذه الدورة مقدمة على الصورة المصغرة وأهميتها، وما أبرز الخطوات التي يجب اتباعها لإنشائها. ستتعلم أيضًا كيفية إنشاء صور مصغرة متحركة أو باستعمال أحد قوالب كانفا
Coursera
Créer une présentation d’entreprise avec Piktochart
À la fin de ce projet, vous aurez toutes les compétences de base pour créer une présentation d’entreprise professionnelle avec Piktochart, logiciel et outil en ligne de création et d’édition d’infographies et de visuels Marketing en tous genres. Vous serez capable de découvrir en détail les différentes fonctionnalités de la plateforme, et serez en mesure d’utiliser ses outils pour créer une présentation professionnelle, compréhensible et ludique.
AI CERTs
Network and Security Optimization in Telecommunication
This intermediate-level course builds on Pathway A to help you advance from understanding AI concepts to designing and implementing intelligent telecom systems. You’ll dive deep into AI-powered automation, deep learning for anomaly detection, predictive network optimization, and real-time decision intelligence for 5G and IoT ecosystems. Through practical, hands-on exercises, you’ll use tools like Python, TensorFlow, PyTorch, Scikit-learn, Keras, Jupyter Notebooks, and Power BI to develop and deploy AI models that improve network performance, reliability, and customer experience. You’ll also explore how AI can enhance spectrum management, fault prediction, and dynamic resource allocation. Each module blends technical depth with real-world applications, ensuring you learn not just how AI works in telecom, but why it matters. Guided projects and case studies from global telecom providers help you translate insights into measurable outcomes. By the end, you’ll have the skills to design, optimize, and evaluate AI-driven telecom operations at scale — bridging the gap between AI innovation and telecom transformation.
Pearson
Generative AI for Developers: Unit 2
This course teaches you how to use generative AI tools such as ChatGPT and GitHub Copilot in your Python projects. You will learn practical methods for automating scripting tasks, improving data analysis with Jupyter and Pandas, and building web applications. The course covers using AI for writing, testing, and documenting code, as well as creating effective prompts. Each module focuses on skills you can apply directly to your work. By the end of the course, you will understand how to integrate generative AI tools into your Python workflow to improve efficiency and solve problems.
Coursera
Behavioural Base Safety
Behavioural Base Safety: Observing, Coaching, and Reinforcing Safe Workplace Behaviors is an intermediate-level course designed for safety professionals, supervisors, and operational leaders who want to reduce workplace incidents by focusing on human behavior. Traditional compliance-based approaches often fail to engage employees effectively; this course teaches how to transform observations into actionable feedback, reinforce positive behaviors, and build a proactive safety culture. Through expert-led videos, real-world case studies from organizations that successfully applied BBS frameworks, and hands-on exercises, you'll learn to design structured observation systems, provide timely and constructive feedback, implement reinforcement strategies, and monitor behavioral trends. By the end of the course, you'll be able to implement practical Behavior-Based Safety programs that improve workplace engagement, minimize at-risk behaviors, and enhance overall safety performance.
DeepLearning.AI
Serverless Agentic Workflows with Amazon Bedrock
Agentic workflows handle unpredictable tasks based on user input, like making API calls. A serverless architecture efficiently manages these tasks and varying workloads without maintaining servers, enabling faster deployment. You will learn to protect sensitive information and shield customers from harmful content by employing agents with guardrails. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails. The serverless setup is ideal for agents that might need to access many tools or APIs on demand. You’ll explore this through hands-on examples where you’ll: 1. Build a customer service bot for a fictional tea mug business that can handle tasks like answering queries, retrieving information, and processing orders. 2. Connect multiple types of agent actions, and implement guardrails for responsible operation. 3. Use Amazon Bedrock’s fully managed services to deploy and scale the bot efficiently. The course will implement two elements essential to the deployment of business applications: 1. Serverless deployment to achieve rapid scaling and seamless operation without the need to manage infrastructure. 2. Responsible agent to protect your application from malicious prompts and unintended outputs by configuring guardrails. In detail, here’s what you’ll do: 1. Use Amazon Bedrock to create an AI agent, explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. 2. Connect your customer service agent to services like a CRM to get customer details and log support tickets in real time. 3. Attach a code interpreter to your agent, giving it the ability to perform accurate calculations, where it writes and runs its own Python code to support its response. 4. Implement and configure guardrails to prevent your agent from revealing sensitive information and using inappropriate language. 5. Connect your agent to a repository of customer support documents that discuss many issues that the agent can resolve directly or choose to escalate, if necessary, to a human workflow. 6. Get a walkthrough of the Amazon Bedrock interface in the AWS console to configure agents, set the guardrails, and connect to knowledge databases, all in an easy-to-configure graphical interface. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios, fully serverless, and ready to scale.
Pontificia Universidad Católica del Perú
Propedéutico: Fundamentos para Posgrado en Negocios
Este curso propedéutico está diseñado como un espacio de autoformación para los estudiantes que inician su maestría en Negocios. Su propósito es facilitar la adquisición de conocimientos y herramientas fundamentales que les permitan afrontar con éxito los desafíos académicos del posgrado. A través del desarrollo de habilidades clave como la expresión escrita, el pensamiento matemático y el uso estratégico de herramientas de inteligencia artificial, el curso busca reducir brechas de conocimiento y fortalecer las competencias necesarias para un desempeño académico y profesional sólido.
Google Cloud
Datastream: PostgreSQL Replication to BigQuery
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will replicate data from a PostgreSQL database to BigQuery.
Duke University
Renewable Energy and Green Building Entrepreneurship
Welcome to the course where you learn to launch a new business in the energy, finance, real estate, design, engineering, or environmental sectors, while also helping you create positive environmental and human health impacts around the world. We will integrate tools, trends, and tips from the field of entrepreneurship as a career path for making a difference and generating wealth in the renewable energy and green building sectors. This is not a course about theory. Instead, we focus on real world application, step-by-step advice, and case studies. After completing this course, students will be able to: - Define key business opportunities, challenges, and potential solutions in the renewable energy and green building sectors. - Analyze a successful business in renewable energy or green building. - Identify 2 to 3 problems you might solve with either renewable energy or green building products or services. - Plan for engaging with investors who might finance a new business. - Take real world first steps towards launching a new business or corporate initiative, by applying the 1-page business idea summary template and the Business Model Canvas to generating and refining your own new business ideas.
Princeton University
Computer Science: Algorithms, Theory, and Machines
This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our intent is to demystify computation and to build awareness about the substantial intellectual underpinnings and rich history of the field of computer science. First, we introduce classic algorithms along with scientific techniques for evaluating performance, in the context of modern applications. Next, we introduce classic theoretical models that allow us to address fundamental questions about computation, such as computability, universality, and intractability. We conclude with machine architecture (including machine-language programming and its relationship to coding in Java) and logic design (including a full CPU design built from the ground up). The course emphasizes the relationships between applications programming, the theory of computation, real computers, and the field's history and evolution, including the nature of the contributions of Boole, Shannon, Turing, von Neumann, and others. All the features of this course are available for free. People who are interested in digging deeper into the content may wish to obtain the textbook Computer Science: An Interdisciplinary Approach (upon which the course is based) or to visit the website introcs.cs.princeton.edu for a wealth of additional material. This course does not offer a certificate upon completion.
DeepLearning.AI
Neuronale Netze und Deep Learning
Wenn auch Sie topaktuelle KI für sich nutzen möchten, sind Sie mit diesem Kurs auf dem richtigen Weg. Deep Learning-Pioniere sind vielgefragt und wenn Sie Deep Learning einmal gemeistert haben, stehen Ihnen zahlreiche Karrieremöglichkeiten offen. Deep Learning ist eine neue „Superkraft“, mit der Sie KI-Systeme entwickeln können, die so vor ein paar Jahren gar nicht möglich gewesen wären. Mit diesem Kurs eignen Sie sich die grundlegenden Kenntnisse zu Deep Learning an. Am Ende des Kurses werden Sie die folgenden Fähigkeiten erlangt haben: – Verständnis der wesentlichen Techniktrends, die Deep Learning vorantreiben – Erstellen, Trainieren und Anwenden lückenloser, tiefer neuronaler Netze – Wissen, wie Sie effiziente (vektorisierte) neuronale Netze implementieren – Verständnis der wichtigsten Parameter in der Architektur eines neuronalen Netzes In diesem Kurs erfahren Sie zudem, wie Deep Learning eigentlich funktioniert, da das Konzept hier nicht nur flüchtig oder oberflächlich beschrieben wird Nach Abschluss des Kurses werden Sie in der Lage sein, Deep Learning für Ihre eigenen Anwendungen zu nutzen. Wenn Sie eine berufliche Laufbahn im Bereich KI anstreben, werden Sie nach diesem Kurs zudem grundlegende Fragen in einem Bewerbungsgespräch beantworten können. Dies ist der erste Kurs der Deep Learning-Spezialisierung
Universidad Nacional de Colombia
Aprender de experiencias de cuidadores en condición crónica
El curso "Aprender de experiencias de cuidadores en condición crónica" está dirigido a personas que asumen el rol de cuidar a individuos con enfermedades crónicas, ya sean familiares, profesionales de la salud o interesados en perfeccionar sus habilidades para brindar un cuidado integral y de alta calidad. Con un enfoque práctico y contextualizado, los participantes adquirirán herramientas esenciales para identificar señales de advertencia, comprender el impacto emocional y físico de su rol, y desarrollar estrategias efectivas de autocuidado. Esto no solo mejora su bienestar, sino que también optimiza la calidad de vida del paciente. A través de casos de estudio y evaluaciones prácticas, el curso aborda las dificultades propias del cuidado crónico, ayudando a los participantes a gestionar el estrés y a mantener un equilibrio emocional que es crucial para un entorno de cuidado saludable y sostenible. Mediante métodos de enseñanza interactivos, los cuidadores aprenderán desde experiencias reales, adquiriendo una comprensión profunda y crítica de su papel. Al finalizar, los participantes estarán mejor preparados para enfrentar los desafíos de su labor con una perspectiva renovada, garantizando así un cuidado más eficiente y sostenible.
EDUCBA
Analyze Personal Finance and Private Wealth Strategies
By the end of this course, learners will be able to analyze investor profiles, evaluate risk and return objectives, apply tax-efficient portfolio strategies, and design comprehensive private wealth management solutions. Learners will also be able to assess behavioral factors, construct investment policy statements, interpret simulation-based outcomes, and evaluate estate planning and global wealth transfer considerations. This course provides a structured and practical introduction to personal finance and private wealth management, integrating behavioral finance, investment policy design, taxation, asset allocation, risk management, and estate planning. Through a progressive, module-based approach, learners gain the skills needed to align financial strategies with individual goals, constraints, and psychological profiles. Real-world scenarios, case-based examples, and simulation techniques help bridge theory and application, ensuring learners understand how decisions impact long-term wealth outcomes. What makes this course unique is its holistic focus on the individual investor. Rather than treating investments in isolation, the course connects investor behavior, life stages, tax structures, ownership regimes, and global considerations into a unified decision-making framework. This integrated perspective equips learners with job-relevant skills applicable to financial planning, private banking, wealth advisory, and investment analysis roles.
Coursera
Scikit-Learn to Solve Regression Machine Learning Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means. This project is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your next job interview.
Coursera
Read GA4 Traffic
Read GA4 Traffic: From Users to Channels is a hands-on, intermediate course for marketers and analysts looking to master the fundamentals of traffic analysis in Google Analytics 4. In a digital world overflowing with data, knowing exactly where your audience comes from isn't just useful—it's essential for smart marketing and sustainable growth. This course demystifies GA4 by focusing on the core metrics and reports that matter most. You will start by building a solid foundation, learning to differentiate between a "user" and a "session"—a critical distinction for accurate reporting. From there, you'll dive into a GA4 demo account to navigate the interface with confidence and identify your top-three traffic acquisition channels. Through practical, real-world examples from companies like The New York Times and HubSpot, you will learn not just how to find the data, but how to interpret and communicate its significance. By the end of this course, you will be able to produce a clear, concise traffic report and explain its implications, proving you can deliver actionable insights from GA4. Reading traffic data is not an end goal; it’s the first step in making smarter marketing decisions.