Introduction to Trading, Machine Learning & GCP
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.
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- Duration 10 hours
- Course by Google Cloud
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Offered by
About
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. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. 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).Modules
Meet and Greet
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2
Videos
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2
Readings
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1
Assignment
1
Assignment
- Python Skills Assessment Quiz
2
Videos
- Class Overview - Who these courses are for
- Course Overview Introduction to Trading with Machine Learning on Google Cloud
2
Readings
- Supervised Learning and Regression
- Welcome to Introduction to Trading, Machine Learning and GCP
Machine Learning in Finance and your first model using Google Cloud
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5
Videos
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1
Assignment
1
Assignment
- AI and Machine Learning
5
Videos
- What is AI and ML ? What is the difference between AI and ML?
- Applications of ML in the Real World
- What is ML?
- Game: The importance of good data
- Brief History of ML in Quantitative Finance
Why Google Cloud Platform?
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2
Videos
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1
Readings
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1
Assignment
1
Assignment
- Google Cloud
2
Videos
- Why Google?
- Why Google Cloud Platform?
1
Readings
- Case Study: Capital Markets in the Cloud
Learn ML interactively with Jupyter Notebooks on Cloud AI Platform
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8
Videos
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1
ExternalTool
1
External Tool
- Qwiklabs: Building a Regression Model in AI Platform Notebooks
8
Videos
- What are AI Platform Notebooks
- Using Notebooks
- Benefits of AI Platform Notebooks
- What do we want to model? Let's start simple
- Demo: Building a model with BigQuery ML
- How to use Qwiklabs for your Labs
- Lab Intro: Building a Regression Model
- Lab Walkthrough: Building a Regression Model
Trading Fundamentals: Quant Theory, Arbitrage, and Back-testing
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9
Videos
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1
Assignment
1
Assignment
- Trading Concepts Review
9
Videos
- Trading vs Investing
- The Quant Universe
- Quant Strategies
- Quant Trading Advantages and Disadvantages
- Exchange and Statistical Arbitrage
- Index Arbitrage
- Statistical Arbitrage Opportunities and Challenges
- Introduction to Backtesting
- Backtesting Design
Introduction to Supervised Learning
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6
Videos
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1
ExternalTool
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1
Assignment
1
Assignment
- Forecasting
1
External Tool
- Qwiklabs: Building a Regression Model in BigQuery for AAPL Stock Data
6
Videos
- What is forecasting? - part 1
- What is forecasting? - part 2
- Choosing the right model and BQML - part 1
- Choosing the right model and BQML - part 2
- Lab Intro: Forecasting Stock Prices using Regression in BQML
- Lab Walkthrough: Forecasting Stock Prices using Regression in BQML
Additional Practice: BigQuery Machine Learning model types
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1
Readings
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1
ExternalTool
1
External Tool
- Qwiklabs: Movie Recommendations in BigQuery ML (Additional Practice with BigQuery ML)
1
Readings
- Staying current with BigQuery ML model types
Time Series
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4
Videos
4
Videos
- What is a time series?
- AR - Auto Regressive
- MA - Moving Average
- The Complete ARIMA Model
Comparing Regression to ARIMA
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7
Videos
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1
ExternalTool
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1
Assignment
1
Assignment
- Time Series
1
External Tool
- Qwiklabs: Building an ARIMA Model for a Financial Dataset
7
Videos
- ARIMA compared to linear regression
- How can you get a variety of models from just a single series?
- How to choose ARIMA parameters for your trading model
- Time Series Terminology: Auto Correlation
- Sensitivity of Trading Strategy
- Lab Intro: Forecasting Stock Prices Using ARIMA
- Lab Walkthrough: Forecasting Stock Prices using ARIMA
Deep Learning
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2
Videos
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1
Readings
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1
Discussion
1
Discussions
- Applying ML to Winter Ski Resort Problem
2
Videos
- Short history of ML: Neural Networks
- Short history of ML: Modern Neural Networks
1
Readings
- Example BigQuery ML DNN code
Model Generalization
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2
Videos
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1
Assignment
1
Assignment
- Model generalization
2
Videos
- Overfitting and Underfitting
- Validation and Training Data Splits
Course Recap
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1
Videos
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1
Assignment
1
Assignment
- Recap Quiz
1
Videos
- Course Recap + Preview of next course
Auto Summary
Dive into the fundamentals of trading and machine learning with this professional course on Coursera. Explore key concepts like trend analysis, stop-loss, and quantitative trading strategies, while mastering the use of Google Cloud Platform for building machine learning models. Ideal for those with advanced Python skills, a background in statistics, and knowledge of financial markets, this 600-hour course offers valuable insights into data science and AI. Available with a Starter subscription, it's perfect for professionals looking to enhance their expertise.
Jack Farmer