The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Microsoft
Create Serverless Applications
In this course, you will learn how Azure Functions enable the creation of event-driven, compute-on-demand systems that can be triggered by various external events. You will earn how to leverage functions to execute server-side logic and build serverless architectures. This course will help you prepare for the Microsoft Certified: Azure Developer Associate certification. This course is part of a Specialization intended for developers who want to demonstrate their expertise in all phases of cloud development from requirements, definition, and design; to development, deployment, and maintenance; to performance tuning and monitoring. It is ideal for anyone interested in preparing for the AZ-204: Developing Solutions for Microsoft Azure exam. This is the first course in a program of 8 courses to help prepare you to take the exam. Each course teaches you the concepts and skills that are measured by the exam. By the end of this Professional Certificate program, you will be ready to take and sign-up for the Exam AZ-204: Developing Solutions for Microsoft Azure.
Coursera
Demystifying Oracle Cloud Infrastructure (OCI) Security
Welcome to “Demystifying Oracle Cloud Infrastructure (OCI) Security”—a fast paced course designed to endow you with the knowledge and skills needed to navigate the often-complex landscape of cloud security within Oracle’s robust infrastructure. This course will guide you through the much talked about convoluted layers of security in OCI, demystifying the components and offering hands-on insights into securing your cloud deployments efficiently. Through hands-on labs you'll learn how to Confidently design and implement secure OCI environments, mitigate common security risks and threats ensuring that your cloud resources are protected against constantly evolving threats and you always stay compliant with industry standards. This course is designed for a diverse group of professionals including Team Leaders, Supervisors, Managers, IT professionals, system administrators, cloud architects, security engineers, and Database Administrators. Anyone responsible for managing and securing cloud resources within an organization will benefit from this course, equipping them with the necessary skills to navigate Oracle Cloud Infrastructure (OCI) security effectively. To make the most of this course, learners should have a basic understanding of Oracle Cloud Infrastructure (OCI) and experience with provisioning resources using the OCI Cloud Console. Additionally, familiarity with general security principles is essential, as this course builds on those concepts to explore more advanced OCI security features and practices. By the end of this course, learners will be able to interpret key security principles and how they map to OCI security services, while developing a strategy to deploy Identity and Access Management (IAM) in OCI. They will also learn to construct mechanisms for robust network security, compare various data encryption methodologies, and implement measures to secure data and databases. Additionally, the course will focus on monitoring, threat detection, and the importance of Cloud Security Posture Management to ensure continuous protection of cloud resources.
Coursera
Architect Reusable AI Agent Systems
Architect Reusable AI Agent Systems is an intermediate course for AI engineers and developers who want to move beyond building single-purpose agents and learn to design scalable, modular agent architectures that drive business value. This course teaches advanced system design principles, equipping you to build maintainable AI systems that can evolve with business needs. You will learn to evaluate competing reasoning-loop architectures like ReAct and Reflexion by running data-driven A/B tests to select the optimal design for a specific use-case. Through hands-on labs, you will master the software engineering best practices for creating reusable agent components—the Planner, Memory, and Executor—by defining clear API contracts with typed interfaces. You will leave this course with the ability to design, document, and implement a complete Python package of agent components, ready for integration into a production environment.
Microsoft
Using Microsoft Copilot to Understand Your Customer
This course is the second in a series that aims to transform your marketing capabilities with Microsoft Copilot's GenAI. Its focus is on understanding your customers. In this course, you’ll learn how to train Microsoft Copilot with marketing related data. You’ll then learn how to analyze customer insights and define your customer segments. And lastly, you'll step through the process of using Microsoft Copilot to enhance your targeting efforts across channels. This course covers a wide variety of marketing topics and GenAI that are designed to give you an overview of what’s to come in this specialization. By the end of this course, you’ll be able to: Understand how to train Microsoft Copilot with marketing related data. Analyze customer insights and define personas and customer segments. Apply Microsoft Copilot to enhance your targeting efforts across channels. Required Course Materials: A Copilot license is required to complete this course. If you don’t have a Microsoft 365 Personal or Family license, you can start a free 30-day trial using the link provided in the course.
Akamai Technologies, Inc.
Managing Relational Databases
In Managing Relational Databases, you’ll learn about their structure, design, and use of primary and foreign key fields equipping you with foundational knowledge. Upon completing this course, you’ll be able to: ● Master the use of Structured Query Language (SQL) and use it to analyze database structures ● Create and manage databases, tables, and records ● Conduct data analysis using basic SQL queries, conditional statements, and logical comparison ● Control output data using SQL ● Create complex queries using joins, and subqueries Throughout this course, hands-on labs will provide practical experience in working with SQL and manipulating databases. At the end of this course, you’ll complete a capstone project, allowing you to showcase the knowledge and skills you learned throughout the course.
Insper
Gestão de Dados Científicos
Este curso foi produzido pelo Insper com a colaboração da United States Geological Survey (USGS). Ele tem o objetivo de introduzir o que é Gestão de Dados Científicos e contextualizar atividades necessárias para sua execução, assim como para a elaboração de um plano de gestão de dados, que irá subsidiar a produção de pesquisas alinhadas ao quarto paradigma científico. Com este curso, esperamos que você compreenda ou aperfeiçoe suas habilidades de organização do processo de geração, curadoria e publicação de dados, beneficiando assim a comunidade científica com o reuso de conjuntos de dados científicos e a reprodutibilidade de experimentos. Assim, pretendemos impactar o dia a dia de pesquisadores, docentes, estudantes, bibliotecários e outros profissionais que trabalham com dados, com diferentes níveis de experiência e formação, bem como o resultado das instituições às quais estão associados e a relevância de suas produções científicas. Copie e cole este link no seu navegador e assista ao vídeo de divulgação do curso: https://youtu.be/PfWrf68Tt08
EDUCBA
Recommendation Engine - Basics
This hands-on course guides learners through the complete lifecycle of building a movie recommendation system using Python. Beginning with a conceptual overview of recommendation engines and collaborative filtering techniques, learners will identify real-world applications and articulate how these systems drive personalization across platforms. The course progresses through environment setup using Anaconda and dataset preparation, ensuring participants can organize, configure, and manipulate data efficiently. Using the Surprise library, learners will construct machine learning models, validate performance using cross-validation techniques (including RMSE and MAE), and interpret prediction accuracy. Learners will write Python functions to generate personalized movie predictions, gaining practical experience in model evaluation, prediction logic, and iterable handling using tools like islice. By the end of the course, learners will be able to analyze datasets, implement algorithms, and deploy predictive features in a streamlined and reproducible manner. Through interactive coding and progressive exercises, learners will apply, analyze, and create recommendation solutions applicable in real-world data science workflows.
Vanderbilt University
Integrating Generative AI into Project Management
After taking this course, learners will be able to effectively integrate generative AI tools (Large Language Models, LLMs, like ChatGPT) into their project management workflows to enhance efficiency, communication, and decision-making while maintaining ethical standards and data security. • Learners will be able to apply practical AI-driven solutions to automate repetitive tasks and enhance daily project management operations. • Learners will be able to use generative AI to improve the accuracy of team communication • Learners will be able to identify and address potential ethical concerns and limitations when implementing AI in project management. This course teaches how to effectively integrate generative AI into project management to automate tasks, enhance communication, and maintain ethical standards. Learners will understand the balance between AI capabilities and human expertise, ensuring responsible and efficient project outcomes.
Whizlabs
Getting Started with Microsoft Fabric
Data analytics, powered by robust platforms like Microsoft Fabric and Power BI, is transforming how businesses extract insights and drive decisions. Microsoft Fabric provides a unified environment for data integration, warehousing, and analytics, while Power BI enables the creation of interactive visualizations and reports. These tools streamline data workflows, foster data-driven cultures, and deliver personalized business intelligence, making them essential in today's data-centric world. The "Getting Started with Microsoft Fabric" course is designed for individuals seeking to build a strong foundation in modern data analytics practices using Microsoft's cutting-edge technologies. This course is tailored to provide a comprehensive understanding of Microsoft Fabric and Power BI, equipping you with the skills to excel in data-related roles. Whether you are a budding data analyst, an experienced BI developer, or an IT professional aiming to leverage Microsoft's data ecosystem, this course will provide the knowledge and hands-on experience needed to thrive. This course delivers approximately 6:30-7:00 hours of video lectures, blending theoretical concepts with practical demonstrations. The curriculum is organized into five modules, each further divided into focused lessons. To reinforce learning and assess comprehension, each module includes assignments in the form of quizzes and in-video questions, ensuring an interactive and engaging learning experience. Module 1: Getting started with Microsoft Data Analytics Module 2: Microsoft Fabric: Introduction & Core Components Module 3: Microsoft Fabric: Advanced Data Management and Transformation Techniques Module 4: Microsoft Fabric: Comprehensive Data Transformation and Optimization Techniques Module 5: Microsoft Fabric: Explore, Analyze Data with DAX and Semantic Models This course aims to equip you with foundational Microsoft Fabric skills, positioning you for potential future industry-recognized certifications and demonstrating your expertise in modern data analytics. - -Some of the important benefits of gaining this knowledge. By the end of this course, you will be able to - Validating your knowledge and understanding of Microsoft Fabric's capabilities and data analytics roles. - Demonstrating your practical skills in data ingestion, transformation, modeling, and reporting within the Microsoft ecosystem. - Enhancing your career prospects, opening doors to promotions and new job opportunities in data-driven fields.
Packt
Advanced Concepts in Recursion, Backtracking, and OOP
This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will explore advanced topics in recursion, backtracking, and object-oriented programming (OOP). You’ll dive deep into recursive techniques, starting with basic problems like Fibonacci numbers and binary search, and advancing to more complex challenges like quick sort, merge sort, and maze solving. Through various problem-solving exercises, you'll master recursion’s power to simplify problem-solving and improve efficiency. The course also covers the powerful technique of backtracking, emphasizing how to solve constraint satisfaction problems like Sudoku. You’ll then transition to object-oriented programming, learning about classes, objects, inheritance, encapsulation, and polymorphism—core principles that underpin modern software design. Additionally, the course explores data structures such as linked lists, stacks, queues, and binary trees, with a focus on their application in solving real-world problems. By working through a series of LeetCode problems, you’ll develop a strong grasp of algorithmic thinking and efficient coding techniques, including recursion, backtracking, and OOP. By the end of the course, you will be able to implement advanced recursion techniques, solve backtracking problems, apply object-oriented principles in code, and work with essential data structures like linked lists and binary trees to solve complex algorithmic challenges.
Coursera
Facebook Storytelling: Write Compelling Stories
Writing is at the heart of effective Facebook content. In this course, you’ll learn how to create posts that capture attention, communicate clearly, and spark meaningful engagement. You’ll explore the structure of high-performing posts—from compelling hooks to clear calls-to-action—and apply proven copywriting techniques tailored to Facebook’s Feed. Through expert insights, guided examples, and hands-on practice, you’ll experiment with different formats and use AI tools to brainstorm ideas, refine your writing, and speed up your content creation process. By the end, you’ll be able to: - Structure Facebook posts using the Hook–Body–CTA model - Write clearly and persuasively across multiple post formats - Apply storytelling techniques to enhance audience connection - Use AI tools to support content ideation and copy refinement
University of Colorado Boulder
Effective Communication Capstone Project
In the Effective Communication Capstone learners apply the lessons of Business Writing, Graphic Design, and Successful Presentation to create a portfolio of work that represents their mastery of writing, design, and speaking and that expresses their personal brand. The portfolio includes three individual elements—a written memo, a slide deck, and a presentation—integrated around a single topic. We provide the elements for a basic capstone, but we also invite our learners to create their own project if they so choose. This self-designed "Challenge Capstone" allows learners to engage meaningfully in their world by choosing a project relevant to their current job or by volunteering to write, design, and speak for a social organization of their choice. By successfully undertaking the Capstone, learners will accomplish three main goals: 1. They will hone their writing, design, and speaking skills and build a portfolio for a job search and/or professional application; 2. They will shape these skills into a unique brand identity; and, if they choose, 3. They will undertake a transformative effect in the world around them. Ultimately, the importance of Capstone portfolio is greater than the sum of its individual parts. Its true goal lies in each student’s personal transformation and expression of their best selves. We invite you to unleash your skills and we can't wait to see the results! This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Creo Incubator
Modern Leadership and Decision-Making
Modern leadership requires more than authority it requires awareness, sound judgment, and the ability to adapt your approach to complex, changing environments. In CREO Modern Leadership and Decision-Making Course, you will explore what leadership looks like today, strengthen how you make decisions under uncertainty, and develop a practical leadership philosophy you can apply consistently. You’ll begin with modern leadership architectures and the Tri-Layered Leadership Awareness Framework to sharpen self-awareness, stakeholder awareness, and situational awareness. You’ll then build decision-making capability through tools for navigating uncertainty, delegating with trust, designing productive dialogue, and using indirect influence to create alignment. Finally, you’ll examine core leadership philosophies and techniques, using frameworks such as the Double Lens, Self–Context Alignment, experimentation-based iteration, and crystallisation to integrate different styles into a coherent approach. By the end of the course, you will be able to lead with greater clarity and adaptability, make better decisions in high-pressure contexts, and translate leadership principles into everyday actions that improve outcomes for people and systems.
Coursera
Transform JSON & Fix Time Data
Master the critical data transformation skills that turn messy, real-world data into analysis-ready formats. This course tackles two of the most common yet challenging data quality issues facing analysts today: extracting structured data from complex JSON and fixing timezone inconsistencies that corrupt datasets. This Short Course was created to help data analysis professionals accomplish reliable data preprocessing that enables accurate downstream analytics. By completing this course, you'll be able to confidently handle the data wrangling challenges that cause delays and errors in production analytics pipelines. You'll transform from struggling with nested data structures to efficiently processing complex JSON with pandas, and from manually detecting time discrepancies to systematically correcting timezone offsets that fragment user sessions. By the end of this course, you will be able to: Apply scripting techniques to flatten nested JSON data into relational columns. Analyze time-based data to correct inconsistencies arising from timezone offsets. This course is unique because it focuses on real production data quality issues using hands-on Python transformations that mirror actual workplace scenarios, not theoretical exercises. To be successful in this project, you should have a background in Python programming, basic pandas operations, and familiarity with data analysis workflows.
Packt
Getting Started in Port Scanning Using Nmap and Kali Linux
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Delve into the world of network security with a practical approach to port scanning using Nmap and Kali Linux. The course begins by introducing you to the powerful toolset of Kali Linux and the fundamentals of Nmap, enabling you to understand and execute various network security operations. You will explore how to use Nmap for versioning, scanning, and working with complementary tools like Wireshark, setting the groundwork for more advanced techniques. As you progress, the course covers host discovery methods using Nmap, highlighting the differences in functionality between standard and root users. You will gain hands-on experience with host lists, learn to optimize scans for specific needs, and understand the intricate details of port selection and output interpretation. By the end of this section, you will be proficient in selecting and configuring different scan types to get the most out of Nmap’s capabilities. The final part of the course focuses on protecting your system using Ansible in conjunction with Kali Linux. You will learn configuration management to secure your servers, automate firewall setups, and protect SSH servers. The course concludes with a comprehensive summary, reinforcing your newfound skills and preparing you for practical application in real-world scenarios. This course is designed for aspiring cybersecurity professionals, network administrators, and IT enthusiasts looking to gain practical experience in port scanning and network security. A basic understanding of networking concepts and Linux is recommended, including familiarity with IP addressing, subnetting, and command-line operations. No prior experience with Nmap or Kali Linux is required, making this course accessible to beginners eager to develop foundational cybersecurity skills.
University of Pennsylvania
AI Fundamentals for Non-Data Scientists
In this course, you will go in-depth to discover how Machine Learning is used to handle and interpret Big Data. You will get a detailed look at the various ways and methods to create algorithms to incorporate into your business with such tools as Teachable Machine and TensorFlow. You will also learn different ML methods, Deep Learning, as well as the limitations but also how to drive accuracy and use the best training data for your algorithms. You will then explore GANs and VAEs, using your newfound knowledge to engage with AutoML to help you start building algorithms that work to suit your needs. You will also see exclusive interviews with industry leaders, who manage Big Data for companies such as McDonald's and Visa. By the end of this course, you will have learned different ways to code, including how to use no-code tools, understand Deep Learning, how to measure and review errors in your algorithms, and how to use Big Data to not only maintain customer privacy but also how to use this data to develop different strategies that will drive your business.