Informações sobre o curso
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100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 14 horas para completar

Sugerido: 19 hours/week...

Inglês

Legendas: Inglês

Habilidades que você terá

Machine LearningFinanceTradingInvestment

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 14 horas para completar

Sugerido: 19 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
1 hora para concluir

Introduction to Trading, Machine Learning and GCP

13 vídeos (Total 57 mín.), 1 leitura, 3 testes
13 videos
Trading vs Investing6min
The Quant Universe2min
Quant Strategies7min
Quant Trading Advantages and Disadvantages4min
Exchange and Statistical Arbitrage8min
Index Arbitrage2min
Statistical Arbitrage Opportunities and Challenges5min
Introduction to Backtesting5min
Backtesting Design6min
What is AI and ML ? What is the difference between AI and ML?58s
Applications of ML in the Real World1min
What is ML?3min
1 leituras
Welcome to Introduction to Trading, Machine Learning and GCP10min
3 exercícios práticos
Introduction to Trading5min
Python Skills Assessment Quiz
Intro to AI and ML5min
Semana
2
3 horas para concluir

Supervised Learning and Forecasting

13 vídeos (Total 72 mín.), 3 testes
13 videos
Regression and classification11min
Short history of ML: Linear Regression7min
Short history of ML: Perceptron5min
Lab Intro: Building a Regression Model37s
Introduction to Qwiklabs3min
Lab Walkthrough: Building a Regression Model9min
What is forecasting? - part 15min
What is forecasting? - part 24min
Choosing the right model and BQML - part 13min
Choosing the right model and BQML - part 22min
Lab Intro: Forecasting Stock Prices using Regression in BQML36s
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12min
1 exercício prático
Forecasting
Semana
3
2 horas para concluir

Time Series and ARIMA Modeling

11 vídeos (Total 52 mín.), 2 testes
11 videos
AR - Auto Regressive7min
MA - Moving Average2min
The Complete ARIMA Model4min
ARIMA compared to linear regression7min
How can you get a variety of models from just a single series?1min
How to choose ARIMA parameters for your trading model4min
Time Series Terminology: Auto Correlation4min
Sensitivity of Trading Strategy4min
Lab Intro: Forecasting Stock Prices Using ARIMA32s
Lab Walkthrough: Forecasting Stock Prices using ARIMA7min
1 exercício prático
Time Series
Semana
4
1 hora para concluir

Introduction to Neural Networks and Deep Learning

9 vídeos (Total 36 mín.), 3 testes
9 videos
Short history of ML: Modern Neural Networks8min
Overfitting and Underfitting6min
Validation and Training Data Splits4min
Why Google?1min
Why Google Cloud Platform?2min
What are AI Platform Notebooks1min
Using Notebooks1min
Benefits of AI Platform Notebooks2min
3 exercícios práticos
Model generalization
Google Cloud
Module Quiz8min
3.8
55 avaliações

Principais avaliações do Introduction to Trading, Machine Learning & GCP

por AAJan 13th 2020

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

por CRJan 2nd 2020

Other courses recommended before doing this one! Basics of ML, Basics of the stock market, python and sql

Instrutores

Imagem do instrutor, Jack Farmer

Jack Farmer

Curriculum Director
New York Institute of Finance
Imagem do instrutor, Ram Seshadri

Ram Seshadri

Machine Learning Consultant
Google Cloud Platform

Sobre 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....

Sobre 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....

Sobre Programa de cursos integrados 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 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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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