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所在平台: Udemy |
课程主页: https://www.udemy.com/course/technical-business-analytics-for-agile-decision-making/
课程评论：没有评论
课程名称：商业分析师训练营：Excel、统计、SQL、Tableau 课程概述：欢迎参加我的商业分析/智能课程，此课程包含超过30个实际案例！随着基于人工智能的技术迅速崛起，工作世界正在再次发生变化，行业迫切需要数据驱动的决策，以便灵活应对并与新技术相结合。在本课程中，我将教授您使用免费工具（如Google Sheets（Excel、分析工具包）、MySQL和Tableau（试用版））所需的所有技能！这是一个自学型的入门课程，MBA级别的课程设置适合所有背景的学生。无论您是为就业市场做好准备的学生，是希望提升或转型的资深专业人士，还是希望加速业务增长的企业主，完成本课程后，您将对现代商业运作有根本性的不同理解。我们的课程包括理论视频、动手教程（我们一起完成短期作业）以及深入研究的模拟案例，涵盖广泛主题，包括数据管道、入门/高级电子表格功能与工具、描述性/推断性统计、机器学习、时间序列、SQL、可视化和非技术技能。我将定期更新课程内容，以结合行业突破并根据学生反馈调整材料，以提供优化的学习体验。到课程结束时，您将全面了解商业分析，并掌握使用各种工具和技术分析数据以做出明智的商业决策的方法。 课程内容简介： - 介绍：了解敏捷和人工智能驱动的工作流程如何促进现代商业分析师的角色。 - 数据管道：学习大数据的收集、存储和组织方式。 - 电子表格与描述性统计：探索电子表格和描述性统计，理解正态分布和数据点间的关系。 - 概率：研究随机变量和概率分布，计算统计量并做出决策。 - 推断统计：深入学习推断统计，了解假设检验及基于期望值的决策。 - 机器学习1：介绍机器学习和人工智能，包括线性与非线性回归。 - 时间序列：进行时间序列预测，预测未来事件。 - 机器学习2：学习分类、聚类和强化学习。 - SQL：理解数据库，读取、修改和处理多个表。 - 可视化与呈现：研究商业智能，创建可视化（使用Tableau）并有效呈现数据。 - 非技术技能：评估企业，团队协作，项目优先排序及理解关键绩效指标。 - 结论：快速回顾您所学的所有内容。 准备好进入商业分析的世界了吗？让我们开始吧！感谢Mike Yang的开发审查。
Welcome to my Business Analytics/Intelligence course with over 30+ practical examples! With the meteoric rise of AI-based technologies, the world of work is changing once again to demand data-driven decisions as industries scramble to become agile and augment with new technology. In this course, I will teach you ALL of the necessary skills using free tools such as Google Sheets (Excel, Analysis ToolPak), MySQL, and Tableau (trial)! This is an introductory self-paced course with an MBA-level curriculum tailored to suit students from all backgrounds! Whether you're currently a student preparing for the job market, a seasoned professional looking to up-skill / pivot, or a business owner looking to accelerate your growth, you will finish this course with a fundamentally different understanding of how the world operates today. Our course will consist of theoretical videos, hands-on tutorials where we work through short assignments together, and mock cases to dive into a wide range of topics, including data pipelines, intro/advanced spreadsheets functions + tools, descriptive/inferential statistics, machine learning, time series, SQL, visualization, and nontechnical skills.I will be constantly updating this course with industry breakthroughs regularly, and adjusting materials based on student feedback to provide an optimized learning experience. By the end of this course, you'll have a comprehensive understanding of Business Analytics and how to use various tools and techniques to analyze data and make informed business decisions.So, what exactly will you be learning? Here's a brief breakdown of the course units:Introduction: Welcome to the course where you'll learn about how agile and AI-powered workflows enable the modern agile business analyst.Data Pipeline: You'll learn about big data and how data is collected, stored, and organized. Spreadsheets & Descriptive Statistics: You'll explore spreadsheets and descriptive statistics, understanding normal distributions and relationships between data points. Probability: You'll study random variables and probability distributions, calculating statistics and making decisions. Inferential Statistics: You'll dive into inferential statistics, learning about hypothesis testing and decision making based on expected value. Machine Learning 1: You'll be introduced to machine learning and artificial intelligence, including linear and non-linear regressions. Time Series: You'll forecast with time series and predict future events. Machine Learning 2: You'll learn about classification, clustering, and reinforcement learning. SQL: You'll understand databases, reading, changing and working with multiple tables. Visualization & Presentation: You'll study business intelligence, creating visualizations (Tableau) and presenting data effectively. Non-Technical Skills: You'll evaluate businesses and work within teams, prioritizing projects and understanding KPIs.Conclusion: Quick wrap up of everything that you have learnedAre you ready to dive into the world of Business Analytics? Let's get started!Shoutout to Mike Yang for dev reviews
