CS 351L - AI Lab

Welcome to the AI Lab Course (CS 351L)! In this repository, you will explore various concepts in Artificial Intelligence (AI) through hands-on exercises and projects using Python. The course focuses on practical implementations of AI techniques, algorithms, and tools commonly used in the field of AI and cybersecurity.

📚 Course Overview

• Course Code: CS 351L
• Program: BS Cybersecurity
• Semester: 5th

📋 Course Outline

Throughout the course, we will cover the following topics:

1. Introduction to Python: Variables, Data Types, and Control Structures
2. AI Development Environment: Setting up Google Colab, Introduction to NumPy, Pandas, Matplotlib
3. Supervised Learning: Linear Regression, Classification
4. Unsupervised Learning: K-Means, Hierarchical Clustering
5. Neural Networks: Introduction and Implementation
6. Evaluation Metrics: Precision, Recall, F1-Score
7. Hands-on Projects: AI techniques applied to real-world cybersecurity problems
8. Tool Use: WEKA for data mining and machine learning tasks

💡 How to Contribute

We encourage contributions to improve the course material. To contribute:

1. Fork the repository.
2. Create a new branch.
3. Make your changes and submit a pull request.

📧 Contact

For any queries or assistance, feel free to reach out to the course instructor:
Mr. Usama Arshad
GitHub: usamajanjua9

🙋‍♂️ Maintainer

This repository is maintained by:
Hassaan Ali Bukhari
GitHub: b3ta-blocker

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