This course is for finance professionals, investment management professionals, and traders. Alternatively, this course can be for machine learning professionals who seek to apply their craft to trading strategies.
本课程是 Machine Learning for Trading 专项课程 专项课程的一部分
Introduction to Trading, Machine Learning & GCP
提供方
Google ????
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课程信息
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您将获得的技能
Machine LearningFinanceTradingInvestment
100% 在线
立即开始，按照自己的计划学习。
第 1 门课程（共 3 门）
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中级
完成时间大约为16 小时
建议：17 hours/week
英语（English）
字幕：英语（English）
教学大纲 - 您将从这门课程中学到什么
完成时间为 1 小时
Introduction to Trading, Machine Learning and GCP
In this module you will be introduced to the fundamentals of trading. You will also be introduced to machine learning. Machine Learning is both an art that involves knowledge of the right mix of parameters that yields accurate, generalized models and a science that involves knowledge of the theory to solve specific types of problems.
完成时间为 1 小时
13 个视频 （总计 57 分钟）, 1 个阅读材料, 3 个测验
13 个视频
Trading vs Investing6分钟
The Quant Universe2分钟
Quant Strategies7分钟
Quant Trading Advantages and Disadvantages4分钟
Exchange and Statistical Arbitrage8分钟
Index Arbitrage2分钟
Statistical Arbitrage Opportunities and Challenges5分钟
Introduction to Backtesting5分钟
Backtesting Design6分钟
What is AI and ML ? What is the difference between AI and ML?58
Applications of ML in the Real World1分钟
What is ML?3分钟
1 个阅读材料
Welcome to Introduction to Trading, Machine Learning and GCP10分钟
3 个练习
Introduction to Trading5分钟
Python Skills Assessment Quiz
Intro to AI and ML5分钟
完成时间为 3 小时
Supervised Learning and Forecasting
In this module you will be introduced to supervised machine learning and some relevant algorithms commonly applied to trading problems. You will get some hands-on experience building a regression model using BigQuery Machine Learning
完成时间为 3 小时
13 个视频 （总计 72 分钟）
13 个视频
Regression and classification11分钟
Short history of ML: Linear Regression7分钟
Short history of ML: Perceptron5分钟
Lab Intro: Building a Regression Model37
Introduction to Qwiklabs3分钟
Lab Walkthrough: Building a Regression Model9分钟
What is forecasting? - part 15分钟
What is forecasting? - part 24分钟
Choosing the right model and BQML - part 13分钟
Choosing the right model and BQML - part 22分钟
Lab Intro: Forecasting Stock Prices using Regression in BQML36
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12分钟
1 个练习
Forecasting
完成时间为 2 小时
Time Series and ARIMA Modeling
In this module you will learn about ARIMA modeling and how it is applied to time series data. You will get hands-on experience building an ARIMA model for a financial dataset.
完成时间为 2 小时
11 个视频 （总计 52 分钟）
11 个视频
AR - Auto Regressive7分钟
MA - Moving Average2分钟
The Complete ARIMA Model4分钟
ARIMA compared to linear regression7分钟
How can you get a variety of models from just a single series?1分钟
How to choose ARIMA parameters for your trading model4分钟
Time Series Terminology: Auto Correlation4分钟
Sensitivity of Trading Strategy4分钟
Lab Intro: Forecasting Stock Prices Using ARIMA32
Lab Walkthrough: Forecasting Stock Prices using ARIMA7分钟
1 个练习
Time Series
完成时间为 1 小时
Introduction to Neural Networks and Deep Learning
In this module you'll learn about neural networks and how they relate to deep learning. You'll also learn how to gauge model generalization using regularization, and cross-validation. Also, you'll be introduced to Google Cloud Platform (GCP). Specifically, you'll be shown how to leverage GCP for implementing trading techniques.
完成时间为 1 小时
9 个视频 （总计 36 分钟）
9 个视频
Short history of ML: Modern Neural Networks8分钟
Overfitting and Underfitting6分钟
Validation and Training Data Splits4分钟
Why Google?1分钟
Why Google Cloud Platform?2分钟
What are AI Platform Notebooks1分钟
Using Notebooks1分钟
Benefits of AI Platform Notebooks2分钟
3 个练习
Model generalization
Google Cloud
Module Quiz8分钟
审阅
3.9
来自INTRODUCTION TO TRADING, MACHINE LEARNING & GCP的热门评论
由 MS 提供Jan 29, 2020
Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.
由 GG 提供Feb 1, 2020
Giving 4 stars as there were some technical problems with AI Platform in week 3 and could not access the lab work, which is pretty disappointing.
由 MA 提供Dec 25, 2019
Would be nice to have some extra step at the end of the lad to actually build a trading strategy instead of stopping at the fitting of the model
由 BA 提供Mar 15, 2020
Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.
由 MF 提供Jan 20, 2020
A good intro to machine learning in finance. I does not goes very deep, but hat some useful exercises and practice with google cloud.
由 MM 提供Dec 23, 2019
some explanation in trading was hard, it was realy good to be able to test google cloud services, but needs more practical examples
由 ST 提供Jan 14, 2020
Some of the content in Week 4, might be better placed earlier in the course. Other than that it was a great learning experience.
由 AM 提供Mar 7, 2020
Great for beginners! A lot of examples and theories with practices. It let me learn more about the underlying principles.
关于 Google ????
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
关于 ??????
The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks.
关于 Machine Learning for Trading 专项课程
This Specialization is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies.
The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create quantitative trading strategies that you can train and implement. You will also learn how to use reinforcement learning strategies to create algorithms that can update and train themselves.
To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and a basic knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
常见问题
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