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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Machine Learning for Trading program will introduce you to the real-world challenges people face while implementing machine learning-based trading strategies. These strategies include algorithm steps for information gathering to preparing orders.

The Machine Learning for Trading course will familiarise you with applying probabilistic approaches to Machine Learning to trading decisions. The course will cover topics including trade signal generation and asset management, among others. You will learn how to apply statistical approaches like KNN, Regression Trees, and Linear Regression to actual stock trading situations.

The Machine Learning for Trading course is a four-month course by Udacity along with Georgia Tech. It is aimed at helping you complete real-world projects designed by industry experts. You are sure to master AI Algorithms for building a career-ready portfolio and excelling in trade. Most importantly, the course is free.

Arpan Chakraborty and Tucker Balch will be the instructors for the Machine Learning for Trading online programme.

The Highlights

Four-month course
Free course
Online classes
Intermediate level
Self-paced learning
Rich learning content
Taught by Industry Pros
Interactive Quizzes

Programme Offerings

Online Classes
Self-paced Course
Four-month program
Use of Pandas and NumPy
quizzes
Intermediate level study
Rich learning content
Taught By Industry Experts
free course

Courses and Certificate Fees

Certificate Availability
no

You can enroll yourself by logging in or signing up at Udacity and start the course straight away.

Machine Learning for Trading fee structure

Course	Fees
Machine Learning for Trading	FREE

Eligibility Criteria

To enroll yourself in the online course in Machine Learning for Trading, you must have strong coding skills and be familiar with equity markets. However, a finance or machine learning experience is not necessary.

What you will learn

Knowledge of PythonApplication of ML Algorithms

Upon finishing the Machine Learning for Trading course, you will:

Be well-versed in the Computational Investing
Have understood how to manipulate financial data in Python and the use of numerical computing libraries like Pandas and NumPy
Be adept in the machine learning algorithms used for trading

Who it is for

While the Machine Learning for Trading course focuses on Finance and Computer Science, you will benefit from the course even if you come from a Mathematics, Engineering, or Management background.

Admission Details

To enroll yourself in the program in Machine Learning for Trading, you have to follow the steps given below:

Step 1: Go to the course page on https://www.udacity.com/course/machine-learning-for-trading--ud501.

Step 2: Click on “Start Free Course”.

Step 3: Log in or sign up with Google, Facebook, or your email account to enrol yourself.

After following these steps, the course will automatically begin, and you can get started with the first module.

Application Details

All applications for the Machine Learning for Trading Program will be submitted online. To apply, go on to https://www.udacity.com/course/machine-learning-for-trading--ud501 and log in or signup using Google or Facebook account. This will ensure your enrolment, following which you can begin learning. If you’re signing up with your institutional email ID, you need to provide your name, email ID and generate a unique password.

The Syllabus

Instructors

Georgia Tech Frequently Asked Questions (FAQ's)

1: What will be the class schedule for the Machine Learning for Trading course?

The course is a self-paced course since the lectures are pre-recorded, you can access them wherever you are and at whatever time suits you best.

2: What is the course fee for this Trading program?

The Machine Learning for Trading course is a free course. You can simply log in or sign up at Udacity’s website and begin learning.

3: How long is the Machine Learning for Trading course for?

The course is a four-month course. While it is a self-paced course, you are required to complete it within four months, although you can finish it early too.

4: What will be the evaluation criteria for the course?

The evaluation criteria for the Machine Learning for Trading online course will include interactive quizzes throughout the course.

5: How is the course beneficial for Finance and Computer Science students?

The Machine Learning for Trading program is beneficial for Finance and Computer Science students because it will help them use their existing knowledge of Machine Learning from the perspective of trading.