+- Softwarez.Info - Software's World! (https://softwarez.info)
+-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone)
+--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials)
+--- Thread: Reinforcement Learning for Algorithmic Trading with Python (/Thread-Reinforcement-Learning-for-Algorithmic-Trading-with-Python--523937)
Reinforcement Learning for Algorithmic Trading with Python - BaDshaH - 08-27-2024
![[Image: 4aeb351675ef562ad0f1f9abb931493a.jpg]](https://i123.fastpic.org/big/2024/0827/3a/4aeb351675ef562ad0f1f9abb931493a.jpg)
Published 8/2024
Created by Alexander Hagmann
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 103 Lectures ( 8h 13m ) | Size: 5 GB
Train and test RL Agents for Trading. For RL Beginners with simple Gamification examples and ChatGPT assistance.
What you'll learn:
Train and test a Reinforcement Learning (RL) Agent for (Algorithmic) Trading
Learn and understand the Basics of RL with gamified Fun Projects
Utilize ChatGPT for Reinforcement Learning Projects
Installation and Set-Up for RL with Python and OpenAI´s Gymnasium Library
Strengths and Weaknesses of RL (compared to ML and DL)
RL Use Cases and Algorithms
Understand and master Q-Learning and Q-Tables for complex RL projects
Identify and manage RL Pitfalls such as Overfitting and Performance Plateaus
Requirements:
An internet connection capable of streaming HD videos.
Solid Python Coding Skills (incl. Pandas, Numpy, Matplotlib)
Some Data Science or Machine Learning related background (not required but it helps)
Description:
Reinforcement Learning (RL) is a cutting-edge AI technique, ideal for Algorithmic Trading, but often daunting for beginners. This course is tailored specifically for those new to RL, addressing common challenges like complexity, setup, and foundational knowledge.This course will guide you through the key obstacles in mastering RL, equipping you with the skills to design and implement powerful RL agents tailored to your trading strategies.What Makes This Course the Ideal Choice for You:1. Step-by-step guidance through installation and setup, paired with simple, gamified examples that make complex concepts accessible to all.2. Essential RL theory delivered with just the right balance-enough to understand, without overwhelming you.3. Explore how RL outperforms traditional Machine Learning and Deep Learning in specific scenarios, and understand why and when to use it in your trading strategies.4. Harness the power of ChatGPT, your AI assistant, to navigate the complexities of RL. Learn to leverage ChatGPT's vast knowledge to customize solutions for your unique projects.5. Learn from Alexander Hagmann, an industry veteran with deep expertise in both Data Science/AI and Finance/Trading, ensuring you receive insights that are both technically robust and market-relevant.This project-based course offers three hands-on showcase projects, designed to challenge and reinforce your learning. You'll be encouraged to tackle these projects independently, applying what you've learned before diving into the provided solutions.OpenAI´s Mountain Car challengeOpenAI´s Lunar Lander challengeReinforcement Learning for Algorithmic Trading - a real-world exampleBy the end of this course, you will have a robust framework for approaching Reinforcement Learning projects with Python and ChatGPT, armed with both the practical coding skills and the theoretical knowledge to excel.Who Should Enroll? This course is perfect for Algorithmic Traders, Investors, and anyone eager to enhance their skillset with the transformative power of Reinforcement Learning.Are You Ready to Elevate Your AI Capabilities?Enroll now to position yourself at the cutting edge of AI innovation. Transform your career, unlock new opportunities, and confidently embrace the future of AI!
Who this course is for:
(Algorithmic) Traders and Investors seeking to boost their strategies with RL
Beginners seeking to master real-life RL Projects in no time.
Data Scientists interested in boosting their work with Artificial Intelligence and Reinforcement Learning
Homepage