📚 Programming for Artificial Intelligence

Dr. Erick de Jesús Ordaz Rivas
Artificial Intelligence Engineering – FIME, UANL

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🎯 Course Competency

The course Programming for Artificial Intelligence consists of three phases that enable students to develop skills to program basic AI algorithms such as A*, K-Means, or Logistic Regression.

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📌 Phase 1: AI-oriented tools and languages

• Installation and configuration of development environments (VSCode, Anaconda, RStudio).
• Creation and management of virtual environments.
• Use of Git and version control for collaboration.
• Basic programming in Python, following best practices and modular programming.

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📌 Phase 2: Data and operations

• Basic operations for data processing and cleaning.
• Normalization, scaling, handling missing values.
• Vectorized operations for computational efficiency.
• Programming reusable functions.

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📌 Phase 3: Algorithms

• Implementation of classic AI algorithms:
  • A* search.
  • Iterative algorithms like K-Means.
  • Logistic Regression.
• Using flowcharts and pseudocode as development guidelines.

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📂 Repository Structure

📁 Programming-AI
│
├── 📁 AF4/ # Fundamental Activity 4 - Virtual environment + practice files
│ ├── README.md # Activity description and instructions
│ ├── venv/ # Virtual environment for AF4
│ └── src/ # Python scripts for this activity
│
├── 📁 AF5/ # Fundamental Activity 5 - Virtual environment + practice files
│ ├── README.md
│ ├── venv/
│ └── src/
│
├── 📁 AF6/ # Fundamental Activity 6 - Virtual environment + practice files
│ ├── README.md
│ ├── venv/
│ └── src/
│
├── 📁 Final_Project/ # Final integrative project
│ ├── README.md # Project documentation
│ ├── venv/ # Virtual environment for final project
│ ├── data/ # Datasets used in the project
│ └── src/ # Implementation scripts and notebooks
│
├── 📁 Extra_Class_Activities/ # Additional or optional activities outside the syllabus
│ ├── README.md
│ └── examples/ # Example scripts or resources
│
└── requirements.txt # List of Python dependencies

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📝 Tasks and Grading

Activity	Points
Final Integrative Project	30 pts
Fundamental Activity 4	15 pts
Fundamental Activity 5	15 pts
Fundamental Activity 6	15 pts

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⚙️ Technologies and Tools

• Language: Python 3.12
• Development environment: Visual Studio Code
• Virtual environments: venv
• Version control: Git and GitHub
• Main libraries:
  • numpy
  • pandas
  • matplotlib
  • scikit-learn

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🚀 How to Run This Repository

1. Clone the repository:

   git clone https://github.com/user/Programming-AI.git