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中級レベル

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英語

字幕:英語

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Machine LearningFinanceTradingInvestment

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約15時間で修了

推奨:17 hours/week...

英語

字幕:英語

シラバス - 本コースの学習内容

1

1

1時間で修了

Introduction to Trading, Machine Learning and GCP

1時間で修了
13件のビデオ (合計57分), 1 reading, 3 quizzes
13件のビデオ
Trading vs Investing6 分
The Quant Universe2 分
Quant Strategies7 分
Quant Trading Advantages and Disadvantages4 分
Exchange and Statistical Arbitrage8 分
Index Arbitrage2 分
Statistical Arbitrage Opportunities and Challenges5 分
Introduction to Backtesting5 分
Backtesting Design6 分
What is AI and ML ? What is the difference between AI and ML?58
Applications of ML in the Real World1 分
What is ML?3 分
1件の学習用教材
Welcome to Introduction to Trading, Machine Learning and GCP10 分
3の練習問題
Introduction to Trading5 分
Python Skills Assessment Quiz
Intro to AI and ML5 分
2

2

3時間で修了

Supervised Learning and Forecasting

3時間で修了
13件のビデオ (合計72分)
13件のビデオ
Regression and classification11 分
Short history of ML: Linear Regression7 分
Short history of ML: Perceptron5 分
Lab Intro: Building a Regression Model37
Introduction to Qwiklabs3 分
Lab Walkthrough: Building a Regression Model9 分
What is forecasting? - part 15 分
What is forecasting? - part 24 分
Choosing the right model and BQML - part 13 分
Choosing the right model and BQML - part 22 分
Lab Intro: Forecasting Stock Prices using Regression in BQML36
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12 分
1の練習問題
Forecasting
3

3

2時間で修了

Time Series and ARIMA Modeling

2時間で修了
11件のビデオ (合計52分)
11件のビデオ
AR - Auto Regressive7 分
MA - Moving Average2 分
The Complete ARIMA Model4 分
ARIMA compared to linear regression7 分
How can you get a variety of models from just a single series?1 分
How to choose ARIMA parameters for your trading model4 分
Time Series Terminology: Auto Correlation4 分
Sensitivity of Trading Strategy4 分
Lab Intro: Forecasting Stock Prices Using ARIMA32
Lab Walkthrough: Forecasting Stock Prices using ARIMA7 分
1の練習問題
Time Series
4

4

1時間で修了

Introduction to Neural Networks and Deep Learning

1時間で修了
9件のビデオ (合計36分)
9件のビデオ
Short history of ML: Modern Neural Networks8 分
Overfitting and Underfitting6 分
Validation and Training Data Splits4 分
Why Google?1 分
Why Google Cloud Platform?2 分
What are AI Platform Notebooks1 分
Using Notebooks1 分
Benefits of AI Platform Notebooks2 分
3の練習問題
Model generalization
Google Cloud
Module Quiz8 分
3.8
72件のレビューChevron Right

Introduction to Trading, Machine Learning & GCP からの人気レビュー

by 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.

by AAJan 13th 2020

Good course that gives a lot of breadth as an introduction to machine learning in finance. Well put together

講師

インストラクターの画像、Jack Farmer

Jack Farmer 

Curriculum Director
New York Institute of Finance
インストラクターの画像、Ram Seshadri

Ram Seshadri 

Machine Learning Consultant
Google Cloud Platform

Google Cloudについて

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....

ニューヨーク金融金融研究所について

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....

Machine Learning for Trading専門講座について

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 long-term trading strategies, short-term trading strategies, and hedging strategies. 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 foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....
Machine Learning for Trading

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