Ementorhub

What you'll learn

Understand the fundamentals of trading, including the concepts of trend, returns, stop-loss, and volatility.

Define quantitative trading and the main types of quantitative trading strategies.

Understand the basic steps in exchange arbitrage, statistical arbitrage, and index arbitrage.

Understand the application of machine learning to financial use cases.

Skills you'll gain

Applied Machine Learning

Supervised Learning

Deep Learning

Google Cloud Platform

Technical Analysis

Financial Trading

Artificial Neural Networks

Statistical Machine Learning

Artificial Intelligence and Machine Learning (AI/ML)

Machine Learning

Quantitative Research

Financial Modeling

Regression Analysis

Securities Trading

Financial Forecasting

Forecasting

Time Series Analysis and Forecasting

There are 4 modules in this course

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).

Supervised Learning with BigQuery ML

Time Series and ARIMA Modeling

Introduction to Neural Networks and Deep Learning