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.
Ce cours fait partie de la Spécialisation Machine Learning for Trading
Introduction to Trading, Machine Learning & GCP
Offert par
Google Cloud
New York Institute of Finance
À propos de ce cours
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Compétences que vous acquerrez
Machine LearningFinanceTradingInvestment
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Cours 1 sur 3 dans le
Dates limites flexibles
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Niveau intermédiaire
Approx. 16 heures pour terminer
Recommandé : 17 hours/week
Anglais
Sous-titres : Anglais
Offert par
Google Cloud
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.
New York Institute of Finance
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.
Programme du cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
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.
1 heure pour terminer
13 vidéos (Total 57 min), 1 lecture, 3 quiz
13 vidéos
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
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
1 lecture
Welcome to Introduction to Trading, Machine Learning and GCP10 min
3 exercices pour s'entraîner
Introduction to Trading5 min
Python Skills Assessment Quiz
Intro to AI and ML5 min
3 heures pour terminer
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
3 heures pour terminer
13 vidéos (Total 72 min)
13 vidéos
Regression and classification11 min
Short history of ML: Linear Regression7 min
Short history of ML: Perceptron5 min
Lab Intro: Building a Regression Model37s
Introduction to Qwiklabs3 min
Lab Walkthrough: Building a Regression Model9 min
What is forecasting? - part 15 min
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 exercice pour s'entraîner
Forecasting
2 heures pour terminer
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.
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
1 heure pour terminer
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.
1 heure pour terminer
9 vidéos (Total 36 min)
9 vidéos
Short history of ML: Modern Neural Networks8 min
Overfitting and Underfitting6 min
Validation and Training Data Splits4 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
3 exercices pour s'entraîner
Model generalization
Google Cloud
Module Quiz8 min
Avis
3.9
Meilleurs avis pour INTRODUCTION TO TRADING, MACHINE LEARNING & GCP
par MSJan 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.
par GGFeb 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.
par MADec 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
par BAMar 15, 2020
Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.
À propos du Spécialisation Machine Learning for Trading
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).
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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