FinanceTradingInvestmentMachine Learning applied to FinanceAlgorithmic TradingPython ProgrammingMachine LearningReinforcement Learning Model DevelopmentReinforcement Learning Trading Algorithm OptimizationReinforcement Learning Trading Strategy DevelopmentReinforcement Learning Trading Algo Development
Machine Learning for Trading 특화 과정
Start Your Career in Machine Learning for Trading. Learn the machine learning techniques used in quantitative trading.
제공자:
Google 클라우드
New York Institute of Finance
Machine Learning for Trading 특화 과정Google 클라우드배울 내용
Understand the structure and techniques used in machine learning, deep learning, and reinforcement learning (RL) strategies.
Describe the steps required to develop and test an ML-driven trading strategy.
Describe the methods used to optimize an ML-driven trading strategy.
Use Keras and Tensorflow to build machine learning models.
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이 전문 분야 정보
최근 조회 29,020회
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.
응용 학습 프로젝트
The three courses will show you how to create various quantitative and algorithmic trading strategies using Python. By the end of the specialization, you will be able to create and enhance quantitative trading strategies with machine learning that you can train, test, and implement in capital markets. You will also learn how to use deep learning and reinforcement learning strategies to create algorithms that can update and train themselves.
학습자 경력 결과
33%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
25%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
완료하는 데 약 3개월이 걸립니다
권장 학습 속도: 주 4시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
학습자 경력 결과
33%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
25%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
Familiarization with basic concepts in Machine Learning and Financial Markets; advanced competency in Python Programming.
완료하는 데 약 3개월이 걸립니다
권장 학습 속도: 주 4시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
이 전문 분야에는 3개의 강좌가 있습니다.
Introduction to Trading, Machine Learning & GCP
586개의 평가
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks.
Using Machine Learning in Trading and Finance
241개의 평가
This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it.
Reinforcement Learning for Trading Strategies
148개의 평가
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy.
제공자:
Google 클라우드
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.
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