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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/strategic-business-analytics
课程评论：没有评论
课程名称：战略商业分析基础 课程概述： 本课程旨在为希望将统计知识和技术应用于商业环境的学生、商业分析师和数据科学家提供学习支持。适合有统计学背景、能够使用R或其他编程语言，并熟悉数据库和数据分析技术（如回归、分类和聚类）的学员，尤其是想要向商业角色转型的经验丰富的统计学家、分析师和工程师。 课程将涵盖战略商业分析的各个主题，包括市场营销、供应链、信用评分和人力资源分析等多种应用场景。课程强调如何有效生成令人信服的可操作见解，并介绍不同的数据分析工具以适应不同问题的解决。 通过本课程，学员将发展四种能力，即分析能力、信息技术能力、商业能力和沟通能力，最终能够使用分析方法定量描述业务问题、进行相关数据分析，并以可行和高效的方式呈现结论和建议。 先决条件： 1. 能够使用R或进行编程 2. 了解数据库和数据分析的基础知识（回归、分类、聚类） 课程大纲： 1. **战略商业分析导论**：了解课程和教学方法，认识到战略商业分析依赖于IT、分析、商业和沟通四项技能。 2. **数据中的分组查找**：学习如何识别观察数据中的群体，以提升商业效率，借助实例展示各种概念。 3. **导致事件的因素**：运用严格的统计方法理解事件关系的重要性，通过信用评分和人力资源分析两个示例学习如何分析相关性。 4. **预测与预报**：通过各行业的实例，理解预测未来的重要性，包括信用评分和人力资源分析以及使用生存分析进行预测性维护。 5. **推荐生成与优先级排序**：学习如何向商业受众呈现商业分析结果，强调讲述故事的重要性，掌握有效的结构和可视化技巧，为最终的项目展示做好准备。 通过本课程，学员将能够更好地利用数据创造商业价值。
Name:Introduction to Strategic Business Analytics
Description: In this module, we will introduce you to the course and instructional approach. You will learn that Strategic Business Analytics relies on four distinct skills: IT, Analytics, Business and Communication.
Name:Finding groups within Data
Description:In this module, you will learn how identifying groups of observations enables you to improve business efficiency. You will then learn to create those groups in a business-oriented and actionable way. We will use examples to illustrate various concepts. The assessments will also provide you with opportunities to replicate these examples.
Name:Factors leading to events
Description:In this module, you will learn why using rigorous statistical methods to understand the relationship between different events is crucial. We’ll cover two examples: first, using a credit scoring example, you will learn how to derive information about what makes an individual more or less likely to have a strong credit score? Then, in a second example drawn from HR Analytics, you will learn to estimate what makes an employee more or less likely to leave the company. As usual, we invite you to replicate those examples thanks to the recital and to use the assessments provided at the end of the module to strengthen your understanding of these concepts.
Name:Predictions and Forecasting
Description: In this module you will learn more about the importance of forecasting the future. You will learn through examples from various sectors: first, using the previous examples of credit scoring and HR Analytics, you will learn to predict what will happen. Then, you will be introduced to predictive maintenance using survival analysis via a case discussion. Finally, we’ll discuss seasonality in the context of the first example discussed in this MOOC: using analytics for managing your supply chain and logistics better.
Name:Recommendation production and prioritization
Description:So far, you’ve learnt to use Business Analytics to glean important information relevant to the success of your business. In this module, you’ll learn more about how to present your Business Analytics work to a business audience. This module is also important for your final capstone project presentation.You’ll learn that it is important to find an angle, and tell a story.Instead of presenting a list of results that are not connected to each other, you will learn to take your audience by the hand and steer it to the recommendations you want to conclude on.You’ll learn to structure your story and your slides, and master the most used visualization tips and tricks. The assessment at the end of this module will provide an opportunity for you to practice these methods and to prepare the first step of the capstone project.
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.
