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所在平台: Udemy |
课程主页: https://www.udemy.com/course/discover-knowledge/
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课程名称：金融与商业中的数据分析与决策制定 课程概述：本综合课程深入探讨商业分析和智能的领域，旨在为学生提供必要的技能，以在各个商业领域内做出明智的决策并推动战略性举措。通过一系列生动的讲座和实践练习，参与者将探索金融、开放银行、市场营销、运营管理和商业智能等多个领域的关键概念和工具。 第一部分：金融 - 讲座1：数据驱动决策制定：学习有效描述和呈现数据，从而在金融领域内进行明智的决策。 - 讲座2：历史资产负债表分析：深入分析历史资产负债表，以获取财务表现和趋势的见解。 - 讲座3：增值税准备：掌握增值税的准备工作，确保合规并优化财务操作。 - 讲座4：资产可视化：探讨可视化资产数据的技术，以增强理解并促进决策制定。 - 讲座5：股市快速分析：获得快速分析股市数据的技能，以便及时决策。 - 讲座6：项目净现值：学习计算和评估项目的净现值，以评估其财务可行性。 第二部分：开放银行 - 讲座7：从欧洲中央银行获取数据：探索从欧洲中央银行获取数据的方法，以进行分析和获取见解。 - 讲座8：汇率基准货币转换：学习更改汇率的基准货币，以便于跨境交易和财务分析。 - 讲座9：远程数据转换：掌握远程转换数据的技术，以满足特定的商业需求。 第三部分：市场营销 - 讲座10：数据分析周期：理解数据分析的迭代过程及其在市场营销策略中的应用。 - 讲座11：各国人口分析：分析不同国家的人口数据，以为市场营销策略和目标人群提供有效支持。 - 讲座12：客户分析：学习分析客户数据，识别模式、偏好和行为，以便进行有针对性的市场营销活动。 第四部分：运营管理 - 讲座13：数字数据的类型：探讨各种数字数据及其在运营管理中的重要性。 - 讲座14：商业统计基础：获得商业统计基础知识及其在决策中的作用的理解。 - 讲座15：最优原材料预测：学习预测运营管理中所需的最优原材料数量，以提高效率。 第五部分：商业智能工具 - 讲座16：商业智能背景：理解商业智能在增强组织决策和绩效方面的作用。 - 讲座17：Python基础知识：介绍Python编程语言在数据分析和处理中的应用。 - 讲座18：Power BI Excel查询创建：学习使用Excel数据源在Power BI中创建查询。 - 讲座19：Power BI网页源查询创建：探索从网页源创建Power BI查询的过程。 - 讲座20：Power BI SQL Server查询创建：掌握使用SQL Server数据源在Power BI中创建查询的技巧。 - 讲座21：在Power BI中扩展Python脚本：学习在Power BI中扩展Python脚本的高级技术，以增强数据分析。 第六部分：附录 - 讲座22：描述性数据分析：探索描述性数据分析的技术，以获取商业运营的见解。 - 讲座23：维恩分析：理解维恩分析在识别数据集内关系和交集中的应用。 - 讲座24：股市API集成：学习连接和从股市API中检索实时数据进行分析。 - 讲座25：统计度量：掌握均值、中位数、百分位、标准差和方差等统计度量，用于数据分析。 - 讲座26：线性回归：探索线性回归分析的基本概念及其在预测建模中的应用。 - 讲座27：高级线性回归：深入了解线性回归的概念，以应对更复杂的预测建模场景。 本课程提供了一个全面的商业分析和智能的视角，使参与者能够通过数据驱动的决策制定和战略性洞察推动组织成功。
This comprehensive course provides a deep dive into the world of business analytics and intelligence, equipping students with essential skills to make informed decisions and drive strategic initiatives across various business domains. Through a series of engaging lectures and practical exercises, participants will explore key concepts and tools spanning finance, open banking, marketing, operations management, and business intelligence.Section 1: FinanceLecture 1: Data-Driven Decision Making: Learn to describe and present data effectively for informed decision-making in finance.Lecture 2: Historical Balance Sheets Analysis: Delve into the analysis of historical balance sheets to glean insights into financial performance and trends.Lecture 3: Value Added Taxes Preparation: Master the preparation of value-added taxes to ensure compliance and optimize financial operations.Lecture 4: Assets Visualization: Explore techniques for visualizing assets data to enhance understanding and facilitate decision-making.Lecture 5: Stock Market Instant Analysis: Gain the skills to conduct rapid analysis of stock market data for timely decision-making.Lecture 6: Project Net Present Value: Learn how to calculate and evaluate the net present value of projects to assess their financial viability.Section 2: Open BankingLecture 7: Data Retrieval from European Central Bank: Explore methods for fetching data from the European Central Bank for analysis and insights.Lecture 8: Exchange Rate Base Currency Conversion: Learn to change the base currency of exchange rates to facilitate cross-border transactions and financial analysis.Lecture 9: Remote Data Transformation: Acquire techniques for transforming data remotely to meet specific business requirements.Section 3: MarketingLecture 10: Data Analysis Cycle: Understand the iterative process of data analysis and its application in marketing strategies.Lecture 11: Population Analysis of Countries: Analyze population data of different countries to inform marketing strategies and target demographics effectively.Lecture 12: Customer Analysis: Learn to analyze customer data to identify patterns, preferences, and behavior for targeted marketing campaigns.Section 4: Operations ManagementLecture 13: Types of Digital Data: Explore various types of digital data and their significance in operations management.Lecture 14: Fundamentals of Business Statistics: Gain a foundational understanding of business statistics and its role in decision-making.Lecture 15: Optimal Raw Material Prediction: Learn to predict the optimal amount of raw materials required for efficient operations management.Section 5: Business Intelligence ToolsLecture 16: Business Intelligence Context: Understand the role of business intelligence in enhancing organizational decision-making and performance.Lecture 17: Python Essentials for Beginners: Introduction to Python programming language for data analysis and manipulation.Lecture 18: Power BI Excel Query Creation: Learn to create queries in Power BI using Excel data sources.Lecture 19: Power BI Web Source Query Creation: Explore the process of creating queries in Power BI from web sources.Lecture 20: Power BI SQL Server Query Creation: Master the creation of queries in Power BI using SQL Server data sources.Lecture 21: Extending Python Scripts in Power BI: Learn advanced techniques for extending Python scripts within Power BI for enhanced data analysis.Section 6: AppendixLecture 22: Descriptive Data Analysis: Explore techniques for descriptive data analysis to gain insights into business operations.Lecture 23: Venn Analysis: Understand the application of Venn analysis in identifying relationships and intersections within datasets.Lecture 24: Stock Market API Integration: Learn to connect and retrieve data from stock market APIs for real-time analysis.Lecture 25: Statistical Measures: Gain proficiency in statistical measures such as mean, median, percentile, standard deviation, and variance for data analysis.Lecture 26: Linear Regression: Explore the fundamentals of linear regression analysis and its application in predictive modeling.Lecture 27: Advanced Linear Regression: Dive deeper into the concepts of linear regression for more complex predictive modeling scenarios.This course offers a holistic approach to business analytics and intelligence, empowering participants with the knowledge and skills to drive organizational success through data-driven decision-making and strategic insights.
