Deploying Algorithmic Trading Strategies on the Cloud

Master the Art of Deploying Algorithmic Trading Strategies on the Cloud for Automated and Scalable Trading

5.00 (2 reviews)
Udemy
platform
हिन्दी
language
Investing & Trading
category
Deploying Algorithmic Trading Strategies on the Cloud
344
students
1.5 hours
content
Aug 2023
last update
$19.99
regular price

What you will learn

Algorithmic Trading

Basic Python Programming

Linux Command-line Basics

Deploying Algorithmic trading strategies on Oracle Cloud for free.

Setup VS Code Server on Cloud

Why take this course?

Welcome to "Deploying Algorithmic Trading Strategies on the Cloud", a comprehensive course that will teach you how to leverage cloud computing to deploy and scale your algorithmic trading strategies.

In this course, you will start by learning the basics of algorithmic trading and the different types of trading strategies. You will then dive into the world of cloud computing and explore various cloud platforms and services such as AWS, Azure, and GCP.

Next, you will learn how to prepare your algorithmic trading strategies for deployment on the cloud, including how to containerize your code using Oracle Cloud. You will also learn how to manage and optimize your cloud infrastructure for automated trading, including strategies for scaling and load balancing.

Throughout the course, you will have hands-on opportunities to apply your new knowledge through practical exercises and real-world case studies. By the end of this course, you will have a strong understanding of how to deploy and scale algorithmic trading strategies on the cloud, allowing you to automate your trading and potentially increase your profitability.

Whether you are a seasoned trader looking to take your strategies to the next level or a developer interested in learning about cloud-based trading, this course is for you. Join us today and start deploying your algorithmic trading strategies on the cloud!


Reviews

Kshyam
October 1, 2023
Even though the course is free, it is full of useful information. I appreciate your efforts. Please elaborate this further.

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5181132
udemy ID
2/26/2023
course created date
4/6/2023
course indexed date
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