Algorithmic trading relies on computer programs that execute algorithms to automate some or all elements of a trading strategy. Algorithms are a sequence of steps or rules designed to achieve a goal. They can take many forms and facilitate optimization throughout the investment process, from idea generation to asset allocation, trade execution, and risk management.

Machine learning (ML) and Deep Learning (DL) involves algorithms that learn rules or patterns from data to achieve a goal such as minimizing a prediction error.  ML and DL algorithms can extract information from data to support or automate key investment activities. This course will teach the basis of ML and DL used for trading.

Disclaimer

This course is meant for educational. It does not offer any financial advise on investment. We will not be liable for any investment gain or loss.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant

HRD Corp SBL KHAS Claimable for Employers Registered with HRD Corp

Course Code: M1161

Topic 1 Overview of Machine Learning Methodology

• Introduction to Machine Learning

• Machine Learning vs Deep Learning

• Supervised vs Unsupervised Learning

• Machine Learning Implementation Steps

• Target and Features

• Model Training and Prediction

• Metrics to Evaluate Machine Learning Models

Topic 2 Supervised Learning Models and Applications

• The Linear Regression Model

• Logistics Regression Model

• Naïve Bayes Model

• Decision Tree Model

• Random Forest Model

• XGBoost Model

• Neural Network Model

Topic 3 Unsupervised Learning Models and Applications

• K-Means Clustering Model

• Hierarchical Clustering Model

• Principal Component Analysis