John Hopkins University - Introduction to Trading, Machine Learning & GCP
- Offered byCoursera
Introduction to Trading, Machine Learning & GCP at Coursera Overview
Duration | 9 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to Trading, Machine Learning & GCP at Coursera Highlights
- 14% got a tangible career benefit from this course.
- 20% got a pay increase or promotion.
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Introduction to Trading, Machine Learning & GCP at Coursera Course details
- 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).
Introduction to Trading, Machine Learning & GCP at Coursera Curriculum
Introduction to Trading with Machine Learning on Google Cloud
Class Overview - Who these courses are for
Course Overview Introduction to Trading with Machine Learning on Google Cloud
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?
Why Google Cloud Platform?
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 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
Supervised Learning and Regression
Welcome to Introduction to Trading, Machine Learning and GCP
Case Study: Capital Markets in the Cloud
Python Skills Assessment Quiz
AI and Machine Learning
Google Cloud
Trading Concepts Review
Supervised Learning with BigQuery ML
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
Staying current with BigQuery ML model types
Forecasting
Time Series and ARIMA Modeling
What is a time series?
AR - Auto Regressive
MA - Moving Average
The Complete ARIMA Model
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
Time Series
Introduction to Neural Networks and Deep Learning
Short history of ML: Neural Networks
Short history of ML: Modern Neural Networks
Overfitting and Underfitting
Validation and Training Data Splits
Course Recap + Preview of next course
Example BigQuery ML DNN code
Model generalization
Recap Quiz
Introduction to Trading, Machine Learning & GCP at Coursera Admission Process
Important Dates
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