Free

Machine Learning for Trading

Course

Implement machine learning based strategies to make trading decisions using real-world data.

Last Updated March 4, 2022

Prerequisites:

No experience required

Course Lessons

Lesson 1

00-00 Introduction

Lesson 2

01-01 Reading and plotting stock data

Lesson 3

01-02 Working with multiple stocks

Lesson 4

01-03 The power of NumPy

Lesson 5

01-04 Statistical analysis of time series

Lesson 6

01-05 Incomplete data

Lesson 7

01-06 Histograms and scatter plots

Lesson 8

01-07 Sharpe ratio and other portfolio statistics

Lesson 9

01-08 Optimizers: Building a parameterized model

Lesson 10

01-09 Optimizers: How to optimize a portfolio

Lesson 11

02-01 So you want to be a hedge fund manager?

Lesson 12

02-02 Market Mechanics

Lesson 13

02-03 What is a company worth?

Lesson 14

02-04 The Capital Assets Pricing Model (CAPM)

Lesson 15

02-05 How hedge funds use the CAPM

Lesson 16

02-06 Technical Analysis

Lesson 17

02-07 Dealing with Data

Lesson 18

02-08 Efficient Markets Hypothesis

Lesson 19

02-09 The Fundamental Law of active portfolio management

Lesson 20

02-10 Portfolio optimization and the efficient frontier

Lesson 21

03-01 How Machine Learning is used at a hedge fund

Lesson 22

03-02 Regression

Lesson 23

03-03 Assessing a learning algorithm

Lesson 24

03-04 Ensemble learners, bagging and boosting

Lesson 25

03-05 Reinforcement learning

Lesson 26

03-06 Q-Learning

Lesson 27

03-07 Dyna

Lesson 28

Interview with Tammer Kamel

Taught By The Best

Tucker Balch

Instructor

Arpan Chakraborty

Instructor

Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.

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