The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Vanderbilt University
Microservice Architectures
Dive into the world of Microservices Architectures with this comprehensive course, designed to provide a clear understanding of both the theoretical and practical aspects of building scalable and robust systems. Beginning with the concept of program slicing, this course will guide you through the intricacies of Microservices, contrasting them against monolithic systems, and demonstrating the art and science behind their design, deployment, and maintenance. What You'll Learn: Program Slicing and its Relevance: Dive into the foundational concepts of program slicing, its significance in system design, and its relationship with Microservices. Monoliths vs. Microservices: Contrast the architectural styles, understanding the strengths, weaknesses, and practical differences of each approach. Decoupling and Invocation Dynamics: Grasp the intricacies of service decoupling, hidden couplings, and the complexities of service invocation within a Microservices environment. Deployment, Scalability, and Dependency Management: Delve into the challenges and consequences of adopting Microservices, focusing on deployment strategies, scalability issues, and dependency isolation. Building Resilient Systems: Explore client-side load balancing, circuit breakers, fallback strategies, and other resilience techniques to ensure system stability and robustness. Who Should Enroll: Students should have intermediate Java programming experience.
LearnQuest
Fundamentals of Data Analysis
This course is the first of a series that aims to prepare you for a role working in data analytics. In this course, you’ll be introduced to many of the primary types of data analytics and core concepts. You’ll learn about the tools and skills required to conduct data analysis. We’ll go through some of the foundational math and statistics used in data analysis and workflows for conducting efficient and effective data analytics. This course covers a wide variety of topics that are critical for working in data analytics and are designed to give you an introduction and overview as you begin to build relevant knowledge and skills.
Coursera
Text Generation with Cohere: Recognizing Similarities
In this 1-hour long project-based course, you will learn how to install Python packages working with Cohere's API, integrate external APIs like Cohere in a Python script, use embeddings to analyze semantic similarity between text and generate text with Cohere's language models. In today's world, where artificial intelligence and natural language processing are revolutionizing the way we interact with data, understanding how to harness these technologies is more important than ever. This project-based course is designed to immerse you in the world of AI-driven text analysis and generation using Cohere, a cutting-edge language model. Throughout this course, aimed at data enthusiasts and budding AI practitioners, you will learn how to integrate external APIs into a Python script, analyze semantic similarity between texts using embeddings, and generate contextually relevant text with Cohere's language models. By navigating through a series of hands-on tasks, you will create a versatile Python application capable of insightful text analysis and creative text generation. This project stands out because it offers a practical, real-world application of advanced AI techniques in a user-friendly manner. To make the most out of this course, a basic understanding of Python programming is recommended.
Coursera
GenAI for Employee Engagement: Driving Real-Time Insights
What if I told you that AI could read between the lines of employee feedback, uncover hidden insights, and boost workplace engagement like never before? Traditional surveys and engagement strategies often fall short—they capture data, but not the full picture. Now, imagine leveraging Generative AI (GenAI) to analyze sentiment, predict engagement trends, and create data-driven strategies that truly resonate with employees. This course will equip you with the tools to harness GenAI for workplace engagement, helping you transform how you understand and connect with your workforce. You’ll explore AI-powered sentiment analysis, personalized engagement strategies, and real-world case studies that showcase AI-driven success. Through hands-on activities and interactive exercises, you'll gain practical skills to implement GenAI solutions effectively. Whether you’re an HR professional, a leader, or someone passionate about workplace culture, this course will empower you to take engagement to the next level. This course is designed for HR professionals, team leaders, and managers who are committed to creating a more engaging and productive workplace. With a focus on leveraging AI technologies, particularly Generative AI (GenAI), the course bridges the gap between traditional employee engagement methods and emerging digital capabilities. Participants will explore how these technologies can enhance the way organizations understand and support their workforce, with hands-on examples and practical insights tailored to their professional responsibilities. Participants should have a foundational understanding of human resources processes, such as employee lifecycle management, performance reviews, and engagement strategies. However, no previous experience with artificial intelligence or machine learning is required. The course is structured to introduce AI concepts in a simple, accessible manner, ensuring that even those unfamiliar with the technology can grasp its relevance and applications within an HR context. By the end of this course, learners will be equipped to transform their engagement strategies using GenAI tools. They will be able to explain how these tools are reshaping the landscape of employee engagement, utilize AI platforms for real-time feedback collection and analysis, and design responsive strategies to tackle engagement issues proactively. Furthermore, learners will gain the skills to implement and continuously refine AI-driven initiatives that foster long-term morale and employee satisfaction.
LearnQuest
Linux Cloud and DevOps
In this course, we look at Cloud, DevOps and the Linux operating system. The course material is a good for anyone preparing for the Linux Foundation Certified IT Associate (LFCA) exam or just interested in learning more about Linux. This course is the fourth course in a series that aims to prepare you for working as an information technology professional.
Fudan University
网络游戏设计与开发毕业项目
近年来，随着智能手机性能的不断提升，智能手机可以流畅运行画质精美、内容丰富的游戏，手游市场以惊人的速度增长。网易游戏、腾讯游戏等著名游戏公司将重心转移到手游的开发和运营方面。《阴阳师》、《梦幻西游》、《CF穿越火线》、《王者荣耀》等手机网游长居App Store排行榜前列。游戏的成功需要游戏公司对游戏产业、游戏策划以及游戏编程有深层次的理解。《网络游戏设计与开发》专项课程也是重点讲解游戏产业、游戏策划以及游戏编程，让学习者掌握相关知识要点。 《网络游戏设计与开发》毕业项目参考网易游戏研发人员的入职要求，网易游戏内部专家给出的建设性意见，结合专项课程游戏产业、游戏策划、游戏开发知识要点，要求学习者完成手机网游教学项目：慕课英雄3的设计与开发。毕业项目参考当前热门FPS游戏“CF穿越火线手游”和“守望先锋”的游戏功能和特色，使用Unity引擎、Photon网络引擎和PlayFab游戏后台API，完成“慕课英雄3”游戏客户端的开发；毕业项目讲述PlayFab、Segment、Amplitude中间件提供的大数据分析服务，分析慕课英雄3游戏事件数据，监控游戏运营情况；毕业项目讲述游戏数值平衡知识要点，利用数值平衡模型调整慕课英雄3游戏战斗数值，提升游戏平衡性；最后，建议学习者在阿里云虚拟机部署Photon服务器，把慕课英雄3游戏发布到Android应用市场，让更多玩家体验你开发的游戏。 通过《网络游戏设计与开发》毕业项目的学习，学习者对《网络游戏设计与开发》专项课程知识要点有更深入的理解，为入职游戏行业打下扎实的基础。
Coursera
Grab Data Fast with Vertical and Horizontal LOOKUP
Data can come our way in multiple forms and from multiple file types. It’s likely that at some point you will be faced with a data set that includes categories and subcategories under one heading or under headings with nested subheadings. Cutting through the file structure can seem like a time-consuming task, so it is critical to leverage VLOOKUP and HLOOKUP to pull out the needed data quickly. In this course you will understand how lookup tables work and apply VLOOKUP and HLOOKUP formulas to quickly extract data by treating a section of your spreadsheet as a lookup table. You will do this as we work side-by-side in the free-to-use software Google Sheets. By the end of this course, you will understand use cases for using vertical and horizontal lookup to extract data when data sets have categories configured with multiple levels. You will also be able to confidently apply VLOOKUP and HLOOKUP formulas to grab data in any spreadsheet software. 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.
Packt
AWS Certified DevOps Engineer - Professional
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. The AWS Certified DevOps Engineer – Professional course offers a comprehensive guide to mastering the skills needed for the AWS Certified DevOps Engineer exam. It covers essential concepts such as application lifecycle management, continuous integration, and delivery (CI/CD), and automation in the AWS environment. By the end of this course, you will have a strong foundation in provisioning, operating, and managing distributed application systems on AWS. The course begins by introducing core AWS tools such as CodeCommit, CodeBuild, CodeDeploy, and CodePipeline, with hands-on examples to show you how to automate the building, testing, and deploying of applications. You will learn to use these services in tandem for continuous integration and delivery, allowing you to implement modern DevOps workflows efficiently. You'll also explore AWS CodeStar to manage multiple AWS DevOps services in one cohesive platform. Next, the course dives into automation, covering topics like Elastic Beanstalk, ECS, and CloudFormation. You will gain hands-on experience with these services to deploy scalable applications, automate infrastructure management, and manage application lifecycles. The automation section also includes practical guidance on working with Docker containers, and ECS clusters, and using AWS OpsWorks to manage applications throughout their lifecycle. Finally, the course addresses monitoring, logging, and compliance. You'll learn how to monitor your resources with CloudWatch, manage logs, set up alarms, and use AWS Config and Systems Manager for compliance and security. This course will equip you with the tools needed to build, deploy, and maintain secure, scalable, and high-performing applications on AWS.
Pearson
Learn JavaScript: Write Modern Code with JavaScript ESNext
This course will take you on a step-by-step guide that will take you from the basic syntax and concepts of JavaScript, all the way through the more advanced concepts and usage that are covered in technical interviews. It includes the latest advancements in generative AI, offering invaluable insights and tools for developers. JavaScript started as a basic language for performing simple computations on web pages, but it’s now become one of the most popular programming languages. It is a tremendously powerful programming language that can be used for any kind of web development, but also for many other types of development, such as data science, mobile app dev, desktop app dev, and much more. It is a clean, readable programming language that is used everywhere and gaining proficiency in JavaScript makes any developer much more valuable to prospective employers these days.
Coursera
GenAI for Market Research Analysts
GenAI for Market Research Analysts is a comprehensive exploration of how Generative Artificial Intelligence (GenAI) is revolutionizing the field of market research. This course offers an in-depth understanding of the capabilities of GenAI in this domain and provides practical strategies for leveraging these powerful tools in day-to-day market research activities. This course is tailored to market research managers and team leads, market research analysts, and aspiring market researchers. It is ideal for professionals responsible for identifying GenAI opportunities and guiding their teams toward more efficient, innovative practices, those looking to enhance their workflows with GenAI-powered tools, and individuals aiming to future-proof their skills in market research. Participants should have familiarity with fundamental market research concepts and workflows, including data collection methods, data analysis techniques, and market segmentation. Experience with common market research tools and technologies, such as survey platforms and data visualization tools, as well as proficiency in data analysis using tools like Excel or SPSS, will be beneficial. An open mindset towards incorporating Generative AI tools and techniques, along with a willingness to experiment and learn, is essential for maximizing the benefit of this learning experience. By the end of this course, market research analysts will be equipped with the knowledge and skills to harness the transformative potential of GenAI, driving efficiency, innovation, and strategic insights in their work.
Google Cloud
FortiGate: Protecting Google Compute resources
This is a self-paced lab that takes place in the Google Cloud console.” This lab is intended for network administrators implementing network traffic inspection in Google Cloud using FortiGate next-gen firewalls. You will learn the reference architecture and configure inbound, outbound, and east-west traffic inspection using a FortiGate HA cluster.
Coursera
TensorFlow for Beginners: Basic Binary Image Classification
The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as understanding the fundamentals of machine learning/neural network model and its key concepts. Learning how to use TensorFlow for implementing machine learning algorithms, data preprocessing, supervised learning. Additionally, learners develop skills in evaluating and deploying machine learning models using TensorFlow.
Coursera
Ethical Governance & Risk in Agentic AI
Ethical Governance & Risk in Agentic AI is an intermediate-level course designed for professionals who need to navigate the complex landscape of autonomous AI systems while ensuring ethical compliance and responsible deployment. As AI systems become increasingly autonomous, traditional governance approaches break down, creating new categories of risk and accountability challenges. This course equips learners with practical frameworks to assess AI autonomy levels, design adaptive compliance strategies, and build scalable governance structures. Through real-world case studies from IBM, UC Berkeley, and Harvard Business Review, learners explore both the opportunities and risks of agentic AI systems. The course emphasizes practical implementation, providing tools and templates that can be immediately applied in organizational settings. By the end, learners will be able to build comprehensive governance frameworks that balance innovation with responsibility, ensuring AI systems serve human values while driving competitive advantage.
Starweaver
Mastering Endpoint Security & Threat Defense
In today’s evolving cyber threat landscape, every endpoint—whether a laptop, server, cloud workload, or mobile device—represents a potential gateway to sensitive data. Cybercriminals know this, making endpoint security the true front line of defense. This course provides a structured, beginner-friendly introduction to endpoint security, taking you beyond traditional antivirus into modern defenses like EDR, Zero Trust, and insider threat detection. Through real-world scenarios and guided labs inside virtual machines, you’ll gain practical skills using lightweight, open-source tools such as Sysmon, Velociraptor, osquery, and Sigma. Instead of abstract concepts, you’ll work with the same workflows and investigative methods that SOC analysts, sysadmins, and blue teamers use daily. By the end of the course, you’ll know how to design secure endpoint architectures, monitor and correlate logs for advanced threat detection, and apply Zero Trust principles using built-in security features. Whether you’re preparing for certifications like CySA+, Blue Team Level 1, or SC-200, aiming for an entry-level SOC role, or transitioning from system administration into security, this course equips you with the skills to stop real-world attacks and build effective defenses without costly tools.
Packt
Career Transition Strategies - Moving into a New Industry
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. Are you looking to switch industries or pursue a new career path? This course provides the tools and strategies to make your career transition seamless and successful. From building a powerful professional network to mastering the art of job interviews, you'll learn how to leverage your existing skills in a new field. Throughout the course, you will explore effective career planning and industry exploration, gaining clarity and confidence in your decision-making process. In addition, this course combines AI-powered tools and real-world examples, offering unique insights that will support your growth. Targeted at individuals in mid-career stages or professionals seeking a career change, this course equips you with the knowledge and tools needed to succeed in your next role. The course is ideal for professionals with at least a basic understanding of networking and job search strategies who are ready to transition into a new industry. By the end of the course, you will be able to craft a career transition plan, develop networking strategies, use AI tools to improve interview performance, and reflect on personal growth opportunities in your new career.
Northeastern University
Data Warehousing and Integration Part 1
This course will cover various topics in data engineering in support of decision support systems, data analytics, data mining, machine learning, and artificial intelligence. You will study on-premises data warehouse architecture, dimensional modeling of data warehouses, Extract-Transform-Load (ETL) integration from source systems to data warehouse, On-line Analytical Processing (OLAP) systems, and the evolving world of data quality and data governance. It offers you an opportunity to design, develop and maintain cloud-based data pipelines. Both on-premises and cloud-based platforms will be used to illustrate and implement data engineering techniques using operational and analytical data warehouses.