12,053 courses
This course explores the technologies that support modern virtual selling, including CRM systems, growth-focused sales tools, artificial intelligence and ChatGPT. Learners will discover how to improve productivity, automate workflows, strengthen customer engagement and make more informed sales decisions using modern digital technologies.
This course delves into transformative ideas reshaping healthcare delivery. It explores emerging business and medical practice models and the impact of novel information technology, examining how these advancements disrupt existing practices and beliefs. Emphasis is placed on evaluating these innovations to effectively balance cost, quality, and access. Additionally, the course offers practical insights into managing change within the intricate healthcare landscape.
The course covers project performance domains and explores predictive, adaptive, and hybrid approaches. You'll learn about planning techniques, stakeholder management, and building high-performing teams. Understand project life cycles from start to finish and how to tailor processes for specific needs. Our expert-led modules focus on ethical practices, quality management, and effective communication, preparing you to be a capable project manager.
이번 강의에서는 급변하는 글로벌 트렌드와 이 트렌드가 소비자 및 노동 시장, 금융 시스템, 전 세계 국가 간 지정학적 관계에 미치는 영향을 분석합니다. 와튼 스쿨(Wharton School)의 교수 마우로 기옌(Mauro Guillen)이 설계한 이 강의를 통해 비즈니스 세계 및 사회에 이러한 트렌드가 어느 정도의 영향을 미치는지 이해할 수 있을 것입니다. 과거와 현재의 실제 사례 연구를 통해 한 사회의 변화가 다른 사회에 미치는 영향을 살펴봅니다. 이 강좌가 마무리될 즈음에는 비즈니스 및 사회에 영향을 미치는 전 세계적인 변화를 파악 및 분석하고 이에 적응하는 방식을 파악하게 될 것입니다.
How do consumers see your brand relative to your competitors? How should a new product be positioned when it’s launched? Which customer segments are most interested in our current offerings? For these questions and many others, surveys remain the tried and true method for gaining marketing insights. From one-off customer satisfaction surveys to brand tracking surveys that are administered on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers. In Analytic Methods for Survey Data, learners will become familiar with established statistical methods for converting survey responses to insights that can support marketing decisions. Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling. These techniques are presented within the STP (Segmentation, Positioning, Targeting) Framework, enabling learners to apply the analytic techniques to develop a marketing strategy. It is recommended that you complete the Meaningful Marketing Insights course offered by Coursera before taking this course. Note: This course would require using XL Stat, an Excel Add-on that students would need to purchase. XL Stat offers a 30-day free trial, so students could complete this course without incurring additional expense.
This course provides aspiring and early-stage entrepreneurs with a holistic view of what it takes to launch and scale a successful startup. By the end of the course, participants will be able to analyze the critical challenges and decision points that arise in early-stage ventures. From navigating pivotal decisions about product timing and investor partnerships to mastering the art of pitching and valuation, each module offers, real-world examples, and hands-on exercises. By addressing common pitfalls and highlighting key success factors, the series empowers participants to think strategically, make informed decisions, and confidently engage with potential investors.
Note: You should complete all the other courses in this Specialization before beginning this course. This six-week long Project course of the Cloud Computing Specialization will allow you to apply the learned theories and techniques for cloud computing from the previous courses in the Specialization, including Cloud Computing Concepts, Part 1, Cloud Computing Concepts, Part 2, Cloud Computing Applications, Part 1, Cloud Computing Concepts, Part 2, and Cloud Networking.
Reliable geospatial analysis starts with a reliable Python environment. In this short, hands-on course, you’ll learn how to set up, configure, and verify a project-ready Python geospatial stack that supports reproducible, team-based work. Through realistic scenarios and guided activities, you’ll practice installing GeoPandas and Rasterio with conda, creating isolated virtual environments, and applying naming and versioning practices that prevent dependency conflicts. You’ll also build the professional habit of verification by running version-check scripts and interpreting their output to confirm readiness for project kickoff, onboarding, and automated pipelines. Designed for data analysts and data scientists at a beginner level, Setup Python Geo Stack builds your confidence in making environment setup and verification decisions that reduce friction, support collaboration, and ensure your work runs reliably beyond your own machine.
This course examines the current state of the global sports industry through the lenses of fans, revenue models, and technology. Learners will explore how sport evolved from traditional business foundations into a complex, diversified, and data-driven industry shaped by media, sponsorship, digital platforms, and new consumption habits. The course explains how historical models based on ticketing and media rights are giving way to hybrid and data-centric approaches. It also analyzes how fan profiles have become more fragmented, connected, and demanding across generations, creating new challenges and opportunities for sports organizations. Finally, learners will discover how technology is reshaping both on-pitch performance and off-pitch business transformation, from Moneyball and tracking systems to AI-powered fan engagement and decision-making. By the end of the course, participants will have a clear understanding of the major structural shifts transforming sport today and the forces likely to define its future evolution globally.
Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R. With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business. We’ll pay special attention to how you can produce convincing, actionable, and efficient insights. We'll also present you with different data analytics tools to be applied to different types of issues. By doing so, we’ll help you develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication. By the end of this MOOC, you should be able to approach a business issue using Analytics by (1) qualifying the issue at hand in quantitative terms, (2) conducting relevant data analyses, and (3) presenting your conclusions and recommendations in a business-oriented, actionable and efficient way. Prerequisites : 1/ Be able to use R or to program 2/ To know the fundamentals of databases, data analysis (regression, classification, clustering) We give credit to Pauline Glikman, Albane Gaubert, Elias Abou Khalil-Lanvin (Students at ESSEC BUSINESS SCHOOL) for their contribution to this course design.
In the following course, you will explore the dynamics of market competition, where you'll learn strategies to maintain market position against lower-priced competitors. Study case studies, understand economic factors, and delve into benchmarking. Learn to navigate industry disruptions with a deep understanding of competitive interactions and strategy development for change.
By the end of this course, learners will be able to set up ChatGPT environments, integrate the OpenAI API with Python, deploy serverless functions on Azure, and create AI-powered applications using Microsoft Power Automate, Teams, Power Apps, and Bubble.io. They will also design real-world projects such as a MealPlan generator and a Personal Finance assistant. This course provides a step-by-step, hands-on approach that combines coding, automation, and no-code platforms, making it accessible for both beginners and professionals. Learners will benefit from mastering prompt engineering, understanding GPT models, and building practical workflows that bring ChatGPT into real business and personal applications. What makes this course unique is its comprehensive coverage of both low-code/no-code integration and serverless cloud deployment, enabling learners to not only understand the theory but also implement real-world solutions. Whether you are a developer, data enthusiast, or business professional, this course equips you with the skills to transform ChatGPT into powerful, scalable, and customizable applications.
