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所在平台: Coursera专项课程 |
课程主页: https://www.coursera.org/specializations/data-science-investment-professionals
课程评论：没有评论
课程名称：投资专业人士的数据科学 课程概述：该课程旨在帮助投资专业人士或具备相关知识的人士，建立对机器学习技术的基本和实用理解，以及如何将其应用于投资过程中。您将学习描述和评估支撑机器学习技术的统计方法，选择适当的数据可视化，并使用Python创建简单的可视化。课程内容还涵盖如何将机器学习应用于现实投资问题，并向非专业观众解释相关概念和技术。 所获得的技能： - 数据科学 - 伦理 - 机器学习 - Python编程 - 沟通 - 一般统计学 - 统计假设检验 - 逻辑回归建模 - 线性回归建模 - 投资相关统计概念 该专业化课程包括三个模块，涵盖数据可视化、概率概念在投资中的应用、时间序列模型的比较以及机器学习在投资问题中的应用等内容。同时，将学习如何将CFA协会的伦理决策框架应用于机器学习的道德困境中。所有学习内容将帮助您自信地向非专业观众和客户清晰地解释机器学习概念及其实际应用。 应用学习项目：课程中，学习者将使用Python练习计算集中趋势和离散度的量度，创建数据可视化，并了解Python在线性回归和高级回归概念中的应用。同时，通过多项同行评审作业锻炼沟通技能和展现创造力。 课程特性： - 100%在线课程 - 灵活的学习时间和进度 - 初学者级别 - 完成预计需要约5个月，每周建议学习3小时 - 提供可分享的证书 课程链接： 1. 数据和统计基础： [点击这里](https://www.coursera.org/learn/data-statistics-foundation-investment?specialization=data-science-investment-professionals) 2. 投资专业人士的机器学习统计： [点击这里](https://www.coursera.org/learn/statistics-machine-learning-investment?specialization=data-science-investment-professionals) 3. 投资专业人士的机器学习： [点击这里](https://www.coursera.org/learn/machine-learning-investment?specialization=data-science-investment-professionals)
Course: 1
Title:Data and Statistics Foundation for Investment Professionals
Description: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.
Course: 2
Title:Statistics for Machine Learning for Investment Professionals
Description:One of the biggest changes in the past decade is the rapid adoption of machine learning, AI, and big data in investment decision making. This course introduces learners with knowledge of the investment industry to foundational statistical concepts underpinning machine learning as well as advanced AI techniques. This course demonstrates core modeling frameworks along with carefully selected real-world investment practice examples. The course seeks to familiarize learners with two important programming languages — Python and R (no prior knowledge of Python or R necessary). The motivation is to demonstrate the elegance — and speed — simple programming brings to the investment decision-making process. The reading material in this course offers in-practice insights curated from the blogs of CFA Institute as well as other leading publications.
Course: 3
Course Link: https://www.coursera.org/learn/machine-learning-investment?specialization=data-science-investment-professionals
Title:Machine Learning for Investment Professionals
Description:This course is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Incorporating real-life case studies, this course covers both the technical and the “soft skills” necessary for investment professionals to stay relevant.
What you will learn
Describe and evaluate the statistical methods that underpin Machine Learning techniques
Select appropriate data visualizations and create simple visualizations using Python
Describe how Machine Learning applications can address real-world investment problems
Explain machine learning concepts and techniques to a non-expert audience
Skills you will gain
Data Science
Ethics
Machine Learning
Python Programming
Communication
General Statistics
Statistical Hypothesis Testing
Logistic Regression Modeling
Linear Regression Modeling
Statistical Concepts
Investment
About this Specialization
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This Specialization is uniquely tailored to the needs of investment professionals or those with investment industry knowledge who want to develop a basic, practical understanding of machine learning techniques and how they are used in the investment process. Through the three courses, you will learn techniques for presenting data and importance of the “data story”, produce data visualizations using Python, assess and apply probability concepts to investing scenarios, compare simple time-series models and understand their limitations, discover how machine learning applications can address investment problems, and understand how to apply the CFA Institute Ethical Decision-Making Framework to machine learning dilemmas. All that you learn in this Specialization will give you the knowledge and confidence to explain clearly and “translate” machine learning concepts and their application to real-world investment problems to a non-expert audience and clients. Check out this short video overview.
Applied Learning Project
In the courses, learners will use Python to practice calculating measures of central tendency, calculating measures of dispersion, and creating data visualizations as well as see the application of Python in linear regressions and advanced regression concepts. Learners will also practice their communication skills and showcase their creativity in several peer review assignments.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
Background in or knowledge of investment products and firms
Hours to complete
Approximately 5 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Beginner Level
Background in or knowledge of investment products and firms
Hours to complete
Approximately 5 months to complete
Suggested pace of 3 hours/week
Available languages
English
Subtitles: English
