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Building a Workflow for AI

Course

This course introduces learners to the concepts of AI-based trading models. Learners will discover the basic building blocks used to create an AI-based trading model and key Machine Learning techniques they need to be aware of.

This course introduces learners to the concepts of AI-based trading models. Learners will discover the basic building blocks used to create an AI-based trading model and key Machine Learning techniques they need to be aware of.

Intermediate

3 weeks

Completion Certificate

Last Updated October 24, 2024

Skills you'll learn:

Trading signals • Reinforcement learning fundamentals • Basic supervised machine learning • Basic unsupervised learning

Prerequisites:

Basic descriptive statistics • Intermediate Python • Algorithmic trading

Course Lessons

Lesson 1

Introduction to AI Workflows in Trading

Learn how to prepare price data for AI models, backtest trading algorithms, and build a simple RSI algorithm.

Lesson 2

Unsupervised Learning

Explore investment data, summarize key stats, use K-Means and PCA for clustering, adapt trading algorithms, and identify risk factors to enhance model insights on outperformance

Lesson 3

Supervised Learning: Regression

Build regression models using past returns, explore regularization to avoid over/underfitting, and differentiate between training and test data while identifying signs of overfitting and underfitting.

Lesson 4

Supervised Learning: Classification

Predict categorical variables using logistic regression and decision trees. Improve model performance with cross-validation for strong out-of-sample results.

Lesson 5

Reinforcement Learning

Explore reinforcement learning (RL) and its components, Q-learning, the DQN algorithm, and how to build and backtest an RL model.

Taught By The Best

Photo of Metin Akyol

Metin Akyol

Quantitative Analyst

Metin is a Data Scientist and Quantitative Analyst with nearly 10 years of experience in the investment industry, specializing in data-driven investment strategies and AI decision-making. He holds a PhD in Economics from Darmstadt University of Technology and has taught Machine Learning for 5 years.

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