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 Code: CS 351L
- Program: BS Cybersecurity
- Semester: 5th
Throughout the course, we will cover the following topics:
- Introduction to Python: Variables, Data Types, and Control Structures
- AI Development Environment: Setting up Google Colab, Introduction to NumPy, Pandas, Matplotlib
- Supervised Learning: Linear Regression, Classification
- Unsupervised Learning: K-Means, Hierarchical Clustering
- Neural Networks: Introduction and Implementation
- Evaluation Metrics: Precision, Recall, F1-Score
- Hands-on Projects: AI techniques applied to real-world cybersecurity problems
- Tool Use: WEKA for data mining and machine learning tasks
We encourage contributions to improve the course material. To contribute:
- Fork the repository.
- Create a new branch.
- Make your changes and submit a pull request.
For any queries or assistance, feel free to reach out to the course instructor:
- Mr. Usama Arshad
- GitHub: usamajanjua9
This repository is maintained by:
- Syed Muhammad Naqi Raza
- GitHub: naqirraza99