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.
Этот курс входит в специализацию ''Специализация Machine Learning for Trading'
Introduction to Trading, Machine Learning & GCP
от партнера
Google Cloud
Нью-Йоркский институт финансов
Об этом курсе
Недавно просмотрено: 80,093
Приобретаемые навыки
Machine LearningFinanceTradingInvestment
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 1 из 3 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень
Прибл. 16 часа на выполнение
Предполагаемая нагрузка: 17 hours/week
Английский
Субтитры: Английский
Программа курса: что вы изучите
1 ч. на завершение
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 ч. на завершение
13 видео ((всего 57 мин.)), 1 материал для самостоятельного изучения, 3 тестов
13 видео
Trading vs Investing6мин
The Quant Universe2мин
Quant Strategies7мин
Quant Trading Advantages and Disadvantages4мин
Exchange and Statistical Arbitrage8мин
Index Arbitrage2мин
Statistical Arbitrage Opportunities and Challenges5мин
Introduction to Backtesting5мин
Backtesting Design6мин
What is AI and ML ? What is the difference between AI and ML?58
Applications of ML in the Real World1мин
What is ML?3мин
1 материал для самостоятельного изучения
Welcome to Introduction to Trading, Machine Learning and GCP10мин
3 практического упражнения
Introduction to Trading5мин
Python Skills Assessment Quiz
Intro to AI and ML5мин
3 ч. на завершение
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 ч. на завершение
13 видео ((всего 72 мин.))
13 видео
Regression and classification11мин
Short history of ML: Linear Regression7мин
Short history of ML: Perceptron5мин
Lab Intro: Building a Regression Model37
Introduction to Qwiklabs3мин
Lab Walkthrough: Building a Regression Model9мин
What is forecasting? - part 15мин
What is forecasting? - part 24мин
Choosing the right model and BQML - part 13мин
Choosing the right model and BQML - part 22мин
Lab Intro: Forecasting Stock Prices using Regression in BQML36
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12мин
1 практическое упражнение
Forecasting
2 ч. на завершение
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 ч. на завершение
11 видео ((всего 52 мин.))
11 видео
AR - Auto Regressive7мин
MA - Moving Average2мин
The Complete ARIMA Model4мин
ARIMA compared to linear regression7мин
How can you get a variety of models from just a single series?1мин
How to choose ARIMA parameters for your trading model4мин
Time Series Terminology: Auto Correlation4мин
Sensitivity of Trading Strategy4мин
Lab Intro: Forecasting Stock Prices Using ARIMA32
Lab Walkthrough: Forecasting Stock Prices using ARIMA7мин
1 практическое упражнение
Time Series
1 ч. на завершение
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 ч. на завершение
9 видео ((всего 36 мин.))
9 видео
Short history of ML: Modern Neural Networks8мин
Overfitting and Underfitting6мин
Validation and Training Data Splits4мин
Why Google?1мин
Why Google Cloud Platform?2мин
What are AI Platform Notebooks1мин
Using Notebooks1мин
Benefits of AI Platform Notebooks2мин
3 практического упражнения
Model generalization
Google Cloud
Module Quiz8мин
3.9
Рецензии: 86Лучшие отзывы о курсе Introduction to Trading, Machine Learning & GCP
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.
Very good course us introduction to Trading, ML models for trading, ML, Neural networks concept and approaches, Google cloud platform.
О 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.
О Нью-Йоркский институт финансов
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.
Специализация Machine Learning for Trading: общие сведения
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).
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Остались вопросы? Посетите Центр поддержки учащихся.