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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-statistics-foundation-investment
课程评论：没有评论
课程名称：投资专业人士的数据与统计基础 课程概述：该课程旨在为投资专业人士或具有投资行业知识的学习者提供基本数据和统计技术的入门，奠定数据分析的基础，并介绍大数据和机器学习中常用的技术。课程中将涉及主题并提供实用案例，展示投资专业人士如何使用这些技术，包括利用适当的可视化和报告撰写展示“数据故事”的重要性。 你将在本课程中学到如何： - 解释基本统计度量及其在实际数据集中的应用 - 计算和解释离散程度的度量，解释与正态分布的偏差 - 理解不同分布的使用和适用性 - 比较和对比数据可视化的方法，并使用Python创建可视化图（无需先前的Python知识） - 解释抽样理论，并根据样本统计数据推断总体参数 - 针对投资问题制定假设 本课程是CFA Institute提供的数据科学为投资专业人士专业化的一部分。 课程大纲： 1. 中心趋势度量 2. 离散程度度量 3. 分布 4. 数据可视化技术 5. 抽样理论 6. 假设检验 7. 期末项目：该项目使你扮演一名初级分析师的角色，利用所提供的数据进行有意义的操作，并以书面报告的形式向经理呈现你的发现。该项目将考核你在整个课程中学到的多项内容，包括Python，最终评估占总评估的40%。
Part: 1
Title:Measures of Central Tendency
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Part: 2
Title:Measures of Dispersion
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Part: 3
Title:Distributions
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Part: 4
Title:Data Visualization Techniques
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Part: 5
Title:Sampling Theory
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Part: 6
Title:Hypothesis Testing
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Part: 7
Title:Final Project
Description:The final project places you in the role of a junior analyst who has been presented with data and needs to manipulate it in a meaningful way and present your findings to your manager in a well written report. It will test many of the things, including Python, that you have learned throughout this course. This final assessment is worth a maximum of 40% (out of a total of 100%) and counts towards your success in this course.
Aimed at investment professionals or those with investment industry knowledge, this course offers an introduction to the basic data and statistical techniques that underpin data analysis and lays an essential foundation in the techniques that are used in big data and machine learning. It introduces the topics and gives practical examples of how they are used by investment professionals, including the importance of presenting the “data story" by using appropriate visualizations and report writing. In this course you will learn how to: - Explain basic statistical measures and their application to real-life data sets - Calculate and interpret measures of dispersion and explain deviations from a normal distribution - Understand the use and appropriateness of different distributions - Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary) - Explain sampling theory and draw inferences about population parameters from sample statistics - Formulate hypotheses on investment problems This course is part of the Data Science for Investment Professionals Specialization offered by CFA Institute.
