Acerca de este Curso

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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
  • Basic competency in Python, familiarity with the Scikit Learn, Statsmodels and Pandas library. 
  • Familiarity with statistics, financial markets, ML
Aprox. 19 horas para completar
Inglés (English)

Habilidades que obtendrás

Algorithmic TradingPython ProgrammingMachine Learning
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
  • Basic competency in Python, familiarity with the Scikit Learn, Statsmodels and Pandas library. 
  • Familiarity with statistics, financial markets, ML
Aprox. 19 horas para completar
Inglés (English)

ofrecido por

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Instituto de Finanzas de Nueva York

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Google Cloud

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

1 hora para completar

Introduction to Quantitative Trading and TensorFlow

1 hora para completar
4 videos (Total 23 minutos), 1 lectura, 1 cuestionario
4 videos
Basic Trading Strategy Entries and Exits Endogenous Exogenous7m
Basic Trading Strategy Building a Trading Model2m
Advanced Concepts in Trading Strategies6m
1 lectura
Welcome to Using Machine Learning in Trading and Finance10m
1 ejercicio de práctica
Understand Quantitative Strategies
4 horas para completar

Introduction to TensorFlow

4 horas para completar
11 videos (Total 50 minutos)
11 videos
Introduction to TensorFlow6m
TensorFlow API Hierarchy4m
Components of tensorflow Tensors and Variables8m
Getting Started with Google Cloud Platform and Qwiklabs3m
Lab Intro Writing low-level TensorFlow programs43s
Working in-memory and with files3m
Training on Large Datasets with tf.data API4m
Getting the data ready for model training6m
Embeddings8m
Lab Intro Manipulating data with TensorFlow Dataset API34s
Semana
2

Semana 2

3 horas para completar

Training neural networks with Tensorflow 2 and Keras

3 horas para completar
12 videos (Total 53 minutos)
12 videos
Activation functions8m
Activation functions: Pitfalls to avoid in Backpropagation 5m
Neural Networks with Keras Sequential API7m
Serving models in the cloud3m
Lab Intro : Keras Sequential API21s
Neural Networks with Keras Functional API9m
Regularization: The Basics4m
Regularization: L1, L2, and Early Stopping5m
Regularization: Dropout5m
Lab Intro: Keras Functional API38s
Recap57s
Semana
3

Semana 3

6 horas para completar

Build a Momentum-based Trading System

6 horas para completar
12 videos (Total 68 minutos), 1 lectura, 2 cuestionarios
12 videos
Introduction to Hurst8m
Building a Momentum Trading Model7m
Define the Problem9m
Collect the Data2m
Creating Features3m
Split the Data3m
Selecting a Machine Learning Algorithm3m
Backtest on Unseen Data1m
Understanding the Code: Simple ML Strategies to Generate Trading Signal9m
Lab Intro: Momentum Trading43s
Momentum Trading Lab Solution7m
1 lectura
Hurst Exponent and Trading Signals Derived from Market Time Series10m
Semana
4

Semana 4

5 horas para completar

Build a Pair Trading Strategy Prediction Model

5 horas para completar
11 videos (Total 74 minutos)
11 videos
Picking Pairs4m
Picking Pairs with Clustering8m
How to implement a Pair Trading Strategy9m
Evaluate Results of a Pair Trade6m
Backtesting and Avoiding Overfitting6m
Next Steps: Imrovements to your Pair Strategy5m
Lab Intro: Pairs Trading30s
Lab Solution: Pairs Trading7m
Kalman Filter Introduction11m
Kalman Filter Trading Applications6m
1 ejercicio de práctica
Pairs Trading Strategy concepts

Reseñas

Principales reseñas sobre USING MACHINE LEARNING IN TRADING AND FINANCE

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Acerca de Programa especializado: Machine Learning for Trading

Machine Learning for Trading

Preguntas Frecuentes

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