À propos de ce cours

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Niveau intermédiaire

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Approx. 9 heures pour terminer
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Sous-titres : Français, Portugais (brésilien), Russe, Anglais, Espagnol

Compétences que vous acquerrez

FinanceTradingInvestmentMachine Learning applied to Finance
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire

Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.

Approx. 9 heures pour terminer
Anglais
Sous-titres : Français, Portugais (brésilien), Russe, Anglais, Espagnol

Offert par

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Google Cloud

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New York Institute of Finance

Programme du cours : ce que vous apprendrez dans ce cours

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Semaine
1

Semaine 1

4 heures pour terminer

Introduction to Trading with Machine Learning on Google Cloud

4 heures pour terminer
26 vidéos (Total 131 min), 3 lectures, 5 quiz
26 vidéos
Course Overview Introduction to Trading with Machine Learning on Google Cloud5 min
What is AI and ML ? What is the difference between AI and ML?58s
Applications of ML in the Real World1 min
What is ML?3 min
Game: The importance of good data4 min
Brief History of ML in Quantitative Finance11 min
Why Google?1 min
Why Google Cloud Platform?2 min
What are AI Platform Notebooks1 min
Using Notebooks1 min
Benefits of AI Platform Notebooks2 min
What do we want to model? Let's start simple5 min
Demo: Building a model with BigQuery ML25 min
How to use Qwiklabs for your Labs3 min
Lab Intro: Building a Regression Model37s
Lab Walkthrough: Building a Regression Model9 min
Trading vs Investing6 min
The Quant Universe2 min
Quant Strategies7 min
Quant Trading Advantages and Disadvantages4 min
Exchange and Statistical Arbitrage8 min
Index Arbitrage2 min
Statistical Arbitrage Opportunities and Challenges5 min
Introduction to Backtesting5 min
Backtesting Design6 min
3 lectures
Supervised Learning and Regression10 min
Welcome to Introduction to Trading, Machine Learning and GCP10 min
Case Study: Capital Markets in the Cloud10 min
4 exercices pour s'entraîner
Python Skills Assessment Quiz
AI and Machine Learning5 min
Google Cloud
Trading Concepts Review15 min
Semaine
2

Semaine 2

3 heures pour terminer

Supervised Learning with BigQuery ML

3 heures pour terminer
6 vidéos (Total 29 min), 1 lecture, 3 quiz
6 vidéos
What is forecasting? - part 24 min
Choosing the right model and BQML - part 13 min
Choosing the right model and BQML - part 22 min
Lab Intro: Forecasting Stock Prices using Regression in BQML36s
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12 min
1 lecture
Staying current with BigQuery ML model types10 min
1 exercice pour s'entraîner
Forecasting
Semaine
3

Semaine 3

2 heures pour terminer

Time Series and ARIMA Modeling

2 heures pour terminer
11 vidéos (Total 52 min)
11 vidéos
AR - Auto Regressive7 min
MA - Moving Average2 min
The Complete ARIMA Model4 min
ARIMA compared to linear regression7 min
How can you get a variety of models from just a single series?1 min
How to choose ARIMA parameters for your trading model4 min
Time Series Terminology: Auto Correlation4 min
Sensitivity of Trading Strategy4 min
Lab Intro: Forecasting Stock Prices Using ARIMA32s
Lab Walkthrough: Forecasting Stock Prices using ARIMA7 min
1 exercice pour s'entraîner
Time Series
Semaine
4

Semaine 4

1 heure pour terminer

Introduction to Neural Networks and Deep Learning

1 heure pour terminer
5 vidéos (Total 29 min), 1 lecture, 2 quiz
5 vidéos
Short history of ML: Modern Neural Networks8 min
Overfitting and Underfitting6 min
Validation and Training Data Splits4 min
Course Recap + Preview of next course 1 min
1 lecture
Example BigQuery ML DNN code10 min
2 exercices pour s'entraîner
Model generalization
Recap Quiz8 min

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À propos du Spécialisation Machine Learning for Trading

This 3-course Specialization from Google Cloud and New York Institute of Finance (NYIF) 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 (ML) and Python. Alternatively, this program can be for Machine Learning professionals who seek to apply their craft to quantitative trading strategies. By the end of the Specialization, you'll understand how to use the capabilities of Google Cloud to develop and deploy serverless, scalable, deep learning, and reinforcement learning models to create trading strategies that can update and train themselves. As a challenge, you're invited to apply the concepts of Reinforcement Learning to use cases in Trading. This program is intended for those who have an understanding of the foundations of Machine Learning at an intermediate level. To successfully complete the exercises within the program, you should have advanced competency in Python programming and familiarity with pertinent libraries for Machine Learning, such as Scikit-Learn, StatsModels, and Pandas; a solid background in ML and statistics (including regression, classification, and basic statistical concepts) and basic knowledge of financial markets (equities, bonds, derivatives, market structure, and hedging). Experience with SQL is recommended....
Machine Learning for Trading

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