Practical AI with Python and Reinforcement Learning

🚀 Course Title: Practical AI with Python and Reinforcement Learning 🤖

🎉 Headline: Learn how to use Reinforcement Learning techniques to create practical Artificial Intelligence programs!

🔍 Course Description: Please note! This course is in an "early bird" release, and we're still updating and adding content to it, please keep in mind before enrolling that the course is not yet complete.

"The future is already here – it’s just not very evenly distributed." - Marshall McLuhan

Have you ever wondered how Artificial Intelligence actually works? 🤔 Do you want to be able to harness the power of neural networks and reinforcement learning to create intelligent agents that can solve tasks with human level complexity?

This is the ultimate online course for learning how to use Python to harness the power of Neural Networks to create Artificially Intelligent agents! 🧠✨

In this course, we're taking a practical approach that puts you in the driver's seat to actually build and create intelligent agents, rather than just looking at small toy examples like many other online courses. Here we focus on giving you the power to apply artificial intelligence to your own problems, environments, and situations, not just those included in a niche library! 🚘➡️🛠️

Course Highlights:

• Artificial Neural Networks - Dive into the basics of ANNs and understand how they can model complex patterns.
• Convolution Neural Networks (CNNs) - Explore the architecture behind image recognition, text classification, and more!
• Classical Q-Learning - Learn the fundamentals of one of the oldest reinforcement learning algorithms.
• Deep Q-Learning - Discover how to combine deep neural networks with Q-Learning for more complex tasks.
• SARSA - Understand this on-policy algorithm used in Markov decision processes.
• Cross Entropy Methods (CEM) - See how this evolutionary algorithm can optimize stochastic discrete spaces.
• Double DQN - Learn techniques to reduce overestimation in Q-Values by the agent.
• And much more! 🚀

We've designed this course to empower you to create your own deep reinforcement learning agents on your own environments. It focuses on a practical approach with the right balance of theory and intuition with useable code. The course uses clear examples in slides to connect mathematical equations to practical code implementation, before showing how to manually implement the equations that conduct reinforcement learning.

We'll first show you how Deep Learning with Keras and TensorFlow works, before diving into Reinforcement Learning concepts, such as Q-Learning. Then we can combine these ideas to walk you through creating Deep Q-Networks! 🤖💻

There's a lot more to come in this course, and I hope you'll join us inside the course to explore the fascinating world of Reinforcement Learning and AI. Let's embark on this journey together!

Join instructor Jose Portilla for an engaging and comprehensive learning experience in Practical AI with Python and Reinforcement Learning. 🎓✨

Enroll now and be part of the future of AI technology! 🌟