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.
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:
Prerequisites:
Lesson 1
Learn how to prepare price data for AI models, backtest trading algorithms, and build a simple RSI algorithm.
Lesson 2
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
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
Predict categorical variables using logistic regression and decision trees. Improve model performance with cross-validation for strong out-of-sample results.
Lesson 5
Explore reinforcement learning (RL) and its components, Q-learning, the DQN algorithm, and how to build and backtest an RL model.
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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