課程信息

71,055 次近期查看

100% 在線

立即開始,按照自己的計劃學習。

第 1 門課程(共 3 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為16 小時

建議:17 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

Machine LearningFinanceTradingInvestment

100% 在線

立即開始,按照自己的計劃學習。

第 1 門課程(共 3 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為16 小時

建議:17 hours/week...

英語(English)

字幕:英語(English)

提供方

Google 云端平台 徽標

Google 云端平台

纽约金融学院 徽標

纽约金融学院

教學大綱 - 您將從這門課程中學到什麼

內容評分Thumbs Up87%(1,144 個評分)Info
1

1

完成時間為 1 小時

Introduction to Trading, Machine Learning and GCP

完成時間為 1 小時
13 個視頻 (總計 57 分鐘), 1 個閱讀材料, 3 個測驗
13 個視頻
Trading vs Investing6分鐘
The Quant Universe2分鐘
Quant Strategies7分鐘
Quant Trading Advantages and Disadvantages4分鐘
Exchange and Statistical Arbitrage8分鐘
Index Arbitrage2分鐘
Statistical Arbitrage Opportunities and Challenges5分鐘
Introduction to Backtesting5分鐘
Backtesting Design6分鐘
What is AI and ML ? What is the difference between AI and ML?58
Applications of ML in the Real World1分鐘
What is ML?3分鐘
1 個閱讀材料
Welcome to Introduction to Trading, Machine Learning and GCP10分鐘
3 個練習
Introduction to Trading5分鐘
Python Skills Assessment Quiz
Intro to AI and ML5分鐘
2

2

完成時間為 3 小時

Supervised Learning and Forecasting

完成時間為 3 小時
13 個視頻 (總計 72 分鐘)
13 個視頻
Regression and classification11分鐘
Short history of ML: Linear Regression7分鐘
Short history of ML: Perceptron5分鐘
Lab Intro: Building a Regression Model37
Introduction to Qwiklabs3分鐘
Lab Walkthrough: Building a Regression Model9分鐘
What is forecasting? - part 15分鐘
What is forecasting? - part 24分鐘
Choosing the right model and BQML - part 13分鐘
Choosing the right model and BQML - part 22分鐘
Lab Intro: Forecasting Stock Prices using Regression in BQML36
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12分鐘
1 個練習
Forecasting
3

3

完成時間為 2 小時

Time Series and ARIMA Modeling

完成時間為 2 小時
11 個視頻 (總計 52 分鐘)
11 個視頻
AR - Auto Regressive7分鐘
MA - Moving Average2分鐘
The Complete ARIMA Model4分鐘
ARIMA compared to linear regression7分鐘
How can you get a variety of models from just a single series?1分鐘
How to choose ARIMA parameters for your trading model4分鐘
Time Series Terminology: Auto Correlation4分鐘
Sensitivity of Trading Strategy4分鐘
Lab Intro: Forecasting Stock Prices Using ARIMA32
Lab Walkthrough: Forecasting Stock Prices using ARIMA7分鐘
1 個練習
Time Series
4

4

完成時間為 1 小時

Introduction to Neural Networks and Deep Learning

完成時間為 1 小時
9 個視頻 (總計 36 分鐘)
9 個視頻
Short history of ML: Modern Neural Networks8分鐘
Overfitting and Underfitting6分鐘
Validation and Training Data Splits4分鐘
Why Google?1分鐘
Why Google Cloud Platform?2分鐘
What are AI Platform Notebooks1分鐘
Using Notebooks1分鐘
Benefits of AI Platform Notebooks2分鐘
3 個練習
Model generalization
Google Cloud
Module Quiz8分鐘
3.9
86 條評論Chevron Right

來自Introduction to Trading, Machine Learning & GCP的熱門評論

創建者 MSJan 30th 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.

創建者 BAMar 16th 2020

Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.

關於 Machine Learning for Trading 專項課程

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)....
Machine Learning for Trading

常見問題

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

還有其他問題嗎?請訪問 學生幫助中心