The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
SkillUp
Network Traffic Analysis with Wireshark
This course provides hands-on training in network traffic analysis using Wireshark for cybersecurity professionals. You’ll learn to capture, analyze, and interpret network traffic to detect security threats and investigate incidents. Through practical exercises, you’ll gain experience with packet sniffing, protocol analysis, and traffic flow monitoring while working with real-world network data. The curriculum covers essential techniques including Deep Packet Inspection (DPI), traffic filtering, and anomaly detection. You’ll practice identifying malicious patterns like DDoS attacks, port scanning, and data exfiltration attempts. Case studies simulate actual security incidents, teaching you to correlate evidence and trace attack vectors through network traffic. A key focus is developing actionable reporting skills for incident response teams. You’ll learn to document findings, create visualizations of network activity, and present technical details to both security teams and non-technical stakeholders. The course culminates in a capstone project where you analyze a complex traffic capture and produce a professional security assessment report. Designed for aspiring cybersecurity analysts, network administrators, and IT professionals, this training bridges the gap between theoretical knowledge and practical traffic analysis skills. You’ll finish with hands-on experience using industry-standard tools and techniques that are immediately applicable in security operations centers and forensic investigations.
University of Washington
Data Manipulation at Scale: Systems and Algorithms
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales. In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered. You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to: Learning Goals: 1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. 2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models. 3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics 4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends. 5. “Think” in MapReduce to effectively write algorithms for systems including Hadoop and Spark. You will understand their limitations, design details, their relationship to databases, and their associated ecosystem of algorithms, extensions, and languages. write programs in Spark 6. Describe the landscape of specialized Big Data systems for graphs, arrays, and streams
EDUCBA
Statistics for Data Science with Python
By the end of this course, learners will be able to summarize datasets using descriptive statistics, visualize distributions with Python, evaluate probabilities, test hypotheses, and build regression models for predictive analysis. This hands-on training equips learners with the ability to apply statistical thinking to real-world data science projects, ensuring they can analyze, interpret, and present data effectively. The course begins with the foundations of data science and descriptive statistics, covering measures of central tendency, dispersion, correlation, and visualizations using histograms. Learners will then advance into probability and hypothesis testing, mastering concepts such as exclusive events, p-values, test statistics, and error types. Finally, the course culminates in regression and model building, where learners fit models, analyze outputs, evaluate residuals, and apply advanced curve-fitting techniques. What makes this course unique is its practical integration of Pandas and NumPy with statistical theory, enabling learners to not only understand the concepts but also implement them directly in Python. With structured modules and guided exercises, this course bridges the gap between statistical foundations and applied data science, preparing learners for advanced analytics, machine learning, and data-driven decision-making.
Erasmus University Rotterdam
Serious Gaming
Have you ever wondered how playing games can help us to train people, deal with societal challenges or raise awareness of contemporary social issues? In this MOOC you will learn the ins and outs of games that are designed with exactly those purposes in mind: serious games. We will define serious games and discuss the different types that have been developed. We will explain why people like to play them and what impact they may have. State of the art theories from game studies, philosophy and media psychology will be used to help you understand how serious games work and how they appeal to players. The potential impact of gaming is addressed in detail by discussing persuasive games, which aim at changing the player's attitude. Throughout the MOOC, theoretical insights will be illustrated with playful animations and case studies of serious games that are developed by world-class companies in the city of Rotterdam. This MOOC is particularly interesting for you when you are a student considering to study digital media such as serious games, a professional interested in the opportunities these games may create for your organization, or a game developer who wants to know more about the impact serious games can have. Note that this MOOC will not teach you how to design a serious game. Watch the teaser for this MOOC here: https://www.youtube.com/watch?v=FqjY1KSsEx8 Are you ready to broaden your vision on serious games? Join this course and be inspired!
University of Minnesota
Microfabrication Fundamental Processes
Thin-film deposition, lithography, and etching form the most fundamental processes used in microfabrication to create devices. This course introduces these processes, providing learners with an understanding of the techniques, physical phenomena, and material properties that inform fabrication decisions. This course is part of the Semiconductor and MEMS Fabrication Specialization. It is recommended that learners take the previous courses of the Specialization prior to this course. Please disregard module numbers because the content has been reorganized to improve comprehension and flow of the specialization.
Vanderbilt University
AI Agents and Agentic AI with Python & Generative AI
AI Agents Are the Next Leap in Software. Learn to Build Them in Python. AI agents aren't passive tools. They think, act, and solve problems—without waiting for instructions. That's the future of software. And in this course, you'll learn how to build it. Frameworks come and go. Principles last. This course cuts through the noise to teach you how AI agents really work—using Python, the leading language for AI development. Forget tutorials on trendy APIs that'll be dead by next quarter. You'll learn to build AI agents from the ground up. No fluff. No shortcuts. Just the core architecture that powers intelligent systems—knowledge that stays useful no matter how fast the landscape shifts. In this course, you will: - Master Python-based agent architectural fundamentals - Understand the core GAME components (Goals, Actions, Memory, Environment) that make AI agents tick and how they work together in a cohesive Python system - Leverage Python's strengths for efficient agent development - Use Python's dynamic typing, decorators, and metaprogramming to create flexible, maintainable agent frameworks with minimal boilerplate code - Rapidly prototype and implement Python agents - Learn techniques to quickly design Python agent capabilities with prompt engineering before writing a single line of code, then efficiently translate your designs into working Python implementations - Connect Python AI agents to real-world systems - Build Python agents that can interact with file systems, APIs, and other external services - Create Python-powered tool-using AI assistants - Develop Python agents that can analyze files, manage data, and automate complex workflows by combining LLM reasoning with Python's extensive libraries and ecosystem - Build Python developer productivity agents - Create specialized Python agents that help you write code, generate tests, and produce documentation to accelerate your software development process Why Principles Matter More Than Frameworks The AI landscape is changing weekly, but the core principles of agent design remain constant. By understanding how to build agents from scratch, you'll gain: - Transferable knowledge that works across any LLM or AI technology Deep debugging skills because you'll understand what's happening at every level - Framework independence that frees you from dependency on third-party libraries and allows you to succeed with any of them - Future-proof expertise that will still be relevant when today's popular tools are long forgotten By the end of this course, you won't just know how to use AI agents—you'll know how to build them in Python, customize them, and deploy them to solve real business problems. This course will teach you these concepts using OpenAI's APIs, which require paid access, but the principles and techniques can be adapted to other LLMs.
ESSEC Business School
Mieux comprendre l'ESS pour mieux en parler
Journaliste, étudiant, ou citoyen souhaitant mieux connaitre l’économie sociale et solidaire : ce MOOC est fait pour vous. Conçu par l’ESSEC et Reporters d’Espoirs, il vous aidera à mieux définir l’ESS, et à en comprendre l’histoire, l’évolution, les acteurs, les lois que la régissent, et cela afin de mieux en parler. Il vous offrira également des témoignages d’acteurs de terrain - associations, fondations, coopératives, mutuelles, entreprises sociales. Ce cours est divisé en 4 chapitres présentés par Thierry Sibieude, professeur fondateur de la Chaire Innovation et Entrepreneuriat Social. Dans chaque chapitre vous trouverez : - Un module journalistique présenté par Gilles Vanderpooten, journaliste, directeur de Reporters d’Espoirs ; - Le podcast de l'interview d’un acteur de l’ESS par Raphaëlle Duchemin, journaliste ; - Une vidéo grand témoin. Dans ce MOOC, vous apprendrez à : - Définir l’ESS, et comprendre le contexte dans lequel elle évolue ; - Comprendre en quoi l’ESS est un vecteur privilégié de développement durable ; - Définir l’innovation sociale et mieux comprendre le rôle de l’ESS ; - Analyser les modèles économiques rendus possibles par l’ESS ; - Mettre en application ces connaissances pour mieux en parler, que vous soyez journaliste (idées d’angles et de sujets), acteur ou communiquant de l’ESS.
Clemson University
Design and Analysis of Algorithms
The study of algorithms is a significant part of the foundation for the discipline of computing. Over the past several decades, research in algorithmic computer science has advanced at a rapid pace its contributions have had a profound impact on almost every area of science and industry. In this graduate-level course, we aim to provide a modern introduction to the study of algorithms that is both broad and deep. The primary goals of the course are: (1) to become proficient in the application of fundamental algorithm design techniques, as well as the main tools used in the analysis of algorithms, (2) to study and analyze different algorithms for many of the most common types of “standard” algorithmic problems, and (3) to improve one’s ability to implement algorithmic ideas in code.
Automatic Data Processing, Inc. (ADP)
Valuing Excellence
Welcome to Leading StandOut Teams: Valuing Excellence! In this course we’ll discuss how team culture and environment make a big difference to individual and organizational success; help you define success for and with your team; and explore how you can create the conditions that make your team feel comfortable sharing ideas. By the end of the course, you will be able to: - Analyze how team culture affects both individual and organization success. - Define what success looks like for and with your team. - Identify what strengths build success. - Design the conditions to make your team feel comfortable sharing ideas that boost the team's overall productivity, performance, engagement, and more. Modules Include: One: Working Together. Focus on the importance of teams and discuss how team culture and environment make a big difference to individual and organizational success. Two: Aligning on Team Success. Help define success for and with your team. Three: Speaking Up. The environment you create for your team impacts the team's overall productivity, performance, engagement, and so much more. Learn how you can create the conditions that make your team feel comfortable sharing ideas. This is a beginner's course, intended for team leaders with an interest in Leading StandOut Teams. It includes lecture videos by StandOut Strengths Coaches, practice quizzes, graded quizzes, peer-reviewed assignments, discussion prompts, and activity guides to facilitate ongoing learning and provide a structure to make sense of learning so that it can be embedded into real change. To succeed in this course, you should be willing to self-reflect and open to shifting perspectives. Making the effort will result in a positive and fulfilling response.
IESE Business School
Parte 2: Design Thinking para la formulación de problemas
Aprende a identificar y formular problemas relevantes que pueden abordarse con Design Thinking. Este módulo está dirigido a profesionales que buscan aplicar un enfoque estructurado y centrado en el usuario para definir retos complejos.
Emory University
Mastering Business Essentials: Finance
Finance makes the world go around. It helps to raise money for new companies, allocate capital to projects, and provide loans to credit-worthy industries. Finance is also the glue that holds companies together - in charge of the annual budgeting and forecasting processes; when the FP&A department sends you an email, you should respond. Finance is way to assess projects by factoring in the estimates of future cash flows, the risks, timeframe, alternatives, and making smart decisions about money. Any competent executive - whether in Marketing, Sales, Technology, or HR - needs to know that finance basics. Learn the top 20 concepts simply: Time value of money, NPV, DCF, IRR, Comps, discount rate, WACC. Even if you are not a finance-major, you need to know the basics. You need to be able to hold a conversation about finance without losing your cool. Finally, learn the basics of personal finance. Earn money, save, invest, and enjoy.
Coursera
Fundamentals of Speechwriting
Fundamentals of Speechwriting is a course that enhances speechwriting skills by deepening learners’ understanding of the impact of key elements on developing coherent and impactful speeches. It is aimed at learners with experience writing and speaking who wish to enhance their current skills. This course covers strategies for analyzing audience and purpose, selecting style and tone, and incorporating rhetorical appeals and storytelling. Learners will craft openings and closings, build structured outlines, review effective rehearsal techniques, and examine methods for editing and revising. This comprehensive course prepares participants to deliver powerful and persuasive speeches. By the end of this course, learners will be able to: -Identify the elements of speechwriting -Identify common advanced writing techniques for speeches -Identify the parts of a structured speech outline -Identify the role of speech rehearsal, editing, and revising in speechwriting
EDUCBA
TOGAF 10 Foundation
The "TOGAF 10 Foundation" course offers a comprehensive journey through key modules in enterprise architecture. Participants will explore foundational concepts and methodologies essential for successful enterprise architecture practices. The course covers distinctions between TOGAF 9.2 and TOGAF 10, core concepts defining enterprise architecture, and the intricacies of the Architecture Development Method (ADM). Participants will gain proficiency in essential aspects such as architecture governance, stakeholder management, risk management, and business readiness transformation assessment, equipping themselves with the foundational knowledge needed to navigate the dynamic field of enterprise architecture. Target Learners: 1) Enterprise Architects: Professionals already working or aspiring to work in the field of enterprise architecture, responsible for designing and implementing architectural solutions within organizations. 2) IT Professionals: Individuals working in IT departments, including software developers, system administrators, and network engineers, seeking to expand their knowledge of enterprise architecture principles to enhance their roles. 3) Project Managers: Those responsible for overseeing projects within organizations, including planning, execution, and monitoring, who wish to understand how enterprise architecture contributes to project success and alignment with business goals. 4) Individuals Interested in Enterprise Architecture Principles and Methodologies: Anyone with a general interest in enterprise architecture, including students, consultants, and business analysts, looking to gain foundational knowledge in this area. 5) Those Seeking TOGAF Certification: Individuals aiming to obtain TOGAF certification, a globally recognized qualification for enterprise architects, and wanting to prepare for the certification exam. 6) Professionals Aiming to Advance Their Careers in Enterprise Architecture: Individuals looking to advance their careers within the field of enterprise architecture, including those seeking leadership roles or transitioning from other IT-related positions. Pre-requisites: 1) Basic Understanding of Enterprise Architecture Concepts: Familiarity with fundamental enterprise architecture concepts such as business architecture, information architecture, application architecture, and technology architecture. 2) Familiarity with IT Principles: Understanding of core IT principles, including hardware, software, networks, databases, and security concepts. 3) Knowledge of Business Processes: understanding of business processes and operations within organizations, including how different departments function and interact. 4) Understanding of Information Systems: Familiarity with the components and functionalities of information systems, including databases, ERP systems, CRM systems, and other business applications. 5) Familiarity with Project Management Methodologies: Basic knowledge of project management methodologies such as Agile, Waterfall, and Scrum, including project planning, execution, and monitoring techniques. 6) Prior Experience in IT or Related Fields (Beneficial but Not Required): While not mandatory, having prior experience working in IT roles or related fields can facilitate a deeper understanding of the course material and enhance the learning experience.
Google
معالجة البيانات من غير نظيفة إلى نظيفة
هذه هي الدورة التدريبية الرابعة في شهادة تحليلات البيانات من Google. ستزودك هذه الدورات بالمهارات اللازمة للتقدم لوظائف محلل البيانات على المستوى التمهيدي. في هذه الدورة التدريبية، ستستمر في بناء فهمك لتحليلات البيانات والمفاهيم والأدوات التي يستخدمها محللو البيانات في عملهم. ستتعلم كيفية التحقق من بياناتك وتنظيفها باستخدام جداول البيانات وSQL وكذلك كيفية التحقق من نتائج تنظيف البيانات وإبلاغها. سيستمر محللو بيانات Google الحاليون بإرشادك وتزويدك بالطرق العملية لإنجاز مهام محلل البيانات الشائعة باستخدام أفضل الأدوات والموارد. سيتم تجهيز المتعلمين الذين يكملون برنامج الشهادة هذا للتقدم لوظائف المستوى التمهيدي كمحللين بيانات. لا تلزم خبرة سابقة. بنهاية هذه الدورة، ستكون قادرًا على: - تعلم كيفية التحقق من سلامة البيانات. - اكتشاف تقنيات تنظيف البيانات باستخدام جداول البيانات. - إنشاء استعلامات SQL الأساسية للاستخدام مع قواعد البيانات. - تطبيق دوال SQL الأساسية لتنظيف البيانات وتحويلها. - اكتساب فهم لكيفية التحقق من نتائج تنظيف البيانات. - استكشاف عناصر تقارير تنظيف البيانات وأهميتها.
Google Cloud
Model Armor：保護您部署的 AI 應用程式
本課程將複習 Model Armor 的基本安全功能，讓您具備使用這項服務的能力。您將瞭解 LLM 的相關安全風險，以及 Model Armor 如何保護 AI 應用程式。
Google Cloud
애플리케이션에 맞는 Google Cloud 데이터베이스 선택하기
이 과정에서는 Google Cloud에서 애플리케이션을 효과적으로 개발하기 위해 니즈에 맞는 데이터베이스를 분석하고 선택하는 방법을 알아봅니다. 관계형 데이터베이스 및 NoSQL 데이터베이스를 살펴보고 Cloud SQL, AlloyDB, Spanner에 대해 자세히 알아보고 생성형 AI를 포함한 애플리케이션 요구사항에 맞게 데이터베이스의 강점을 활용하는 방법을 배웁니다. 실무형 실습을 통해 벡터 검색을 구성하고 애플리케이션을 클라우드로 마이그레이션해 봅니다.