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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/business-intelligence-data-analytics
课程评论：没有评论
课程名称：商业智能与数据分析：生成洞察 课程概述： 本课程旨在探讨“巨趋势”对当今组织、行业和社会的深远影响，以及如何利用分析工具和技能生成洞察，以助力组织的未来成功。课程将通过结构化学习活动，介绍如何应对这些趋势，并通过以可持续发展为导向的创新来寻找机会。学员将学习系统思维、多层次视角和多学科方法等关键数据分析概念，并应用于实际挑战。同时，课程将重点培养团队合作、与多元利益相关者协作及在伦理决策框架中做出判断的未来技能。 课程大纲： 第一部分：洞察生成基础 本周将强调如何利用数据生成洞察，以帮助个人、企业和政府做出有效决策。 第二部分：基础统计：定量洞察的基础 课程将讲解基本统计概念，这是数据分析的重要组成部分，帮助将定量数据和定性数据转化为可汇总的洞察。 第三部分：正态分布与直方图 学习直方图与正态曲线，应用经验法则快速估算数据分布，同时探讨变量之间的相关性和协方差。 第四部分：数据可视化 研究多种数据可视化技术，学习如何创建易于理解的故事与仪表盘，帮助非分析人员理解数据背后的信息。 第五部分：高级图表与仪表盘 学习创建条形图、子弹图及仪表盘，旨在通过可视化掉噪声并突出关键信息，增强数据故事的传达能力。 第六部分：需求预测 探讨如何利用预测建模生成可操作的洞察，专注于消费者需求预测方法，以便企业能够预见未来结果。 通过该课程，学员将掌握分析与数据可视化技能，更好地应对未来挑战，推动组织成功。
Part: 1
Title:Basics of insight generation
Description:Organisations and governments everywhere want to exploit data to predict behaviors and extract valuable real-world insights. Billions of devices and social media conversations are fueling the rate at which humanity is producing data. Therefore, we need more skills to understand data and make our systems, policies and governance models more efficient. This week we will highlight the potential of generating insights with the help of data in allowing individuals, businesses, and governments to make effective decisions.
Part: 2
Title:Basic statistics: Foundations of quantitative insights
Description:In week 2, we’ll focus on basic statistics. It’s one of the most important components of Data Analytics and it’s crucial to have a clear understanding of all the related concepts to be successful in the data industry. Statistics provide us with a set of tools that offer ways to convert quantitative data and qualitative data into information that we can use to generate insights.
Part: 3
Title:The normal distribution and histograms
Description: Businesses must constantly strive to offer “better” products and services than their competitors. One of the oldest and time-proven techniques by which we can visualise and think about quality in a methodological way is via normal distributions or bell curves. So in week 3, we’ll start by learning about histograms and the normal curve and then have a look at empirical rule which gives us a quick rough estimate about the spread of the given data. Finally, we’ll learn about the measures that quantify the interrelationships between two data variables. Correlation and covariance are two important measures that quantify the relationship between variables and we’ll study both.
Part: 4
Title:Data visualisation
Description:Visualisation is a key technique which can provide answers hidden in data. In this week, you will explore various data visualisations available and how to use them for analysis. These techniques will empower you to create compelling stories and dashboards from your data that the non-analyst community can also understand easily. As a person working in the data industry, you don’t just need to deal with data and solve data-driven problems but the incumbent also needs to convince company executives and government officials of the right decisions to make. These executives/officials may not be well versed in data science, so the incumbent must but be able to present and visualise the data’s story in a way they will understand. And this module will help you achieve that.
Part: 5
Title:Advanced charts and dashboards
Description:This week we learn how to create bar and bullet charts, and dashboards. Data visualization helps to tell stories by curating data into a form easier to understand. A good visualisation tells a story, by removing the noise from data and highlighting the useful information.
Part: 6
Title:Demand forecasting
Description:This week we’ll look at how, by using predictive modelling, we can generate actionable insights that when implemented will provide businesses with a predictable future outcome. Predictive modeling is a group of methods and algorithms that you can employ to forecast an outcome. Utilising basic predictive modelling techniques, we will also explore consumer demand forecasting.
‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation. Via structured learning activities you will explore how these trends can be addressed through sustainability-oriented innovation. You will be introduced to key data analytics concepts such as systems thinking, multi-level perspectives and multidisciplinary methods for envisioning futures, and apply them to specific real-world challenges you and your organisation may face. And there’ll be a focus on future-proofing skills such as teamwork, collaboration with diverse stakeholders and accounting for judgements made within ethical decision-making frameworks.
