Game Hacking With Artificial Intelligence - FPS Aimbot

🎮 Game Hacking With Artlemental Intelligence - FPS Aimbot

Course Headline:

Learn to Create an AI Aimbot for FPS Games Using Yolov5, Mouse Driver Programming, and Data Collection Techniques.

**Critical Notice: The AI model used in this course is designed to detect bots only and should not be employed in online matches. This course material is for educational purposes only. Using the methods described may result in a ban from the game.

Course Instructor: Batuhan ÇERİ

Introduction to Game Hacking with AI:

Artificial Intelligence has been revolutionizing various industries, and the gaming world is no exception. As AI continues to evolve, its integration into games—for both ethical and unethical uses—becomes increasingly significant. With the rise of esports and competitive gaming, the potential for AI to outperform human players grows more apparent every day.

Course Objective:

This course aims to introduce learners to the world of artificial intelligence within gaming, specifically focusing on creating an auto-aiming bot for FPS (First-Person Shooter) games. We'll delve into the technicalities of data collection, model training with Yolov5, detection, and mouse driver programming to enable AI to interact with game environments.

What You Will Learn:

🎯 Key Topics Covered:

• Data Collection: Learn how to gather data effectively from games for your AI project.
• Dataset Labeling: Get hands-on experience in preparing your dataset for the model training process.
• Yolov5 Training: Understand and execute the training of a custom model using the Yolov5 framework.
• Detection with Your Custom Model: Apply your trained model to detect targets within the game.
• Mouse Driver Programming: Write scripts to control mouse input for all games, ensuring versatility and compatibility.

Course Structure:

1. Introduction to AI in Gaming: Explore the intersection of AI and gaming, understanding the implications and potential applications.

2. Data Collection Techniques: Discover methods to collect game data ethically and effectively for training your AI model.

3. Dataset Labeling Process: Learn how to accurately label your dataset, a critical step for successful machine learning outcomes.

4. Yolov5 Training for Detection: Master the process of training your custom model using the state-of-the-art Yolov5 algorithm.

5. Implementation with Real-World Applications: Apply the trained model and mouse driver to achieve real-time target detection and AI-controlled aiming in FPS games.

6. Mouse Driver Programming: Create a universal mouse driver script that can be used across various games, allowing for AI control.

Materials Provided:

All materials necessary for this course are available, including the dataset, scripts, and Arduino Leonardo scripts. The trained model is also provided, ensuring you have everything you need to follow along with the course material.

Prerequisites for Success:

• Basic knowledge of Python programming is recommended to fully understand the code examples.
• Familiarity with installing programs such as cuda and python on your computer will be beneficial for setting up your development environment.

Final Thoughts:

This course is a gateway to understanding the powerful potential of AI within gaming, particularly in the realm of FPS titles. However, it's crucial to remember that using these techniques responsibly and ethically is paramount. The game developers work hard to maintain a fair playing field, and it's important to respect their efforts while learning and experimenting with AI technologies.

Join Batuhan ÇERİ on this insightful journey into the world of game hacking with artificial intelligence. Learn, explore, and expand your understanding of AI's role in gaming—all within the ethical boundaries that protect the integrity of competitive play.