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所在平台: Udemy |
课程主页: https://www.udemy.com/course/applied-data-science-for-finance/
课程评论：没有评论
课程名称：金融应用数据科学 课程概述：本课程旨在帮助希望了解金融与数据科学如何在实际中结合的人们，而无需陷入理论或繁琐公式的困扰。课程开始于Python编程，从基本语法到函数、数据结构和文件处理一应俱全。接着，课程将进入数据预处理环节，讲解如何清理金融数据、处理缺失值、消除异常值，并为分析准备数据。 之后，课程重点介绍在金融中应用的工具，如Pyfolio、MPLFinance、Riskfolio-lib等。学员将使用真实的金融数据构建投资组合分析、风险管理和收益计算模型。我们不使用抽象的玩具数据集，而是直接处理真实的股票数据、基金表现及经济指标。 课程不要求学员具备金融或计算机科学背景，从基础开始，以清晰和结构化的方式解释每个步骤。如果您已经熟悉Python，可以直接跳至金融和项目部分。后续更新将包括R、MATLAB和Julia实现一些关键项目的内容，这使得本课程不仅对学习者有用，也能帮助专业人士比较不同工具。 完成课程后，学员将具备在金融工作流程中使用代码的实际理解，并拥有一套可以实际应用的笔记本。
This course is designed for people who want to understand how finance and data science come together in practice - without getting lost in theory or endless formulas. You'll start with Python, covering everything from basic syntax to functions, data structures, and file handling. Then you'll move into data preprocessing - how to clean financial data, handle missing values, remove outliers, and prepare data for analysis.After that, the course focuses on applied tools used in finance: Pyfolio, MPLFinance, Riskfolio-lib, and others. You'll use real financial data to build models for portfolio analysis, risk management, and return calculation. No abstract toy datasets - we work with real stock data, fund performance, and economic indicators.You don't need a background in finance or computer science. The course starts from the beginning and explains every step in a clear and structured way. And if you already know Python, you can skip ahead to the finance and project sections.Later updates will include R, MATLAB, and Julia implementations for some of the key projects. This makes the course useful not just for learners, but also for professionals looking to compare tools.By the end of the course, you'll have a working understanding of how to use code in financial workflows - and a set of notebooks you can actually use.
