This repository gathers all practical projects developed during my Artificial Intelligence postgraduate program. Each folder contains an independent example project, exploring concepts, techniques, and tools learned throughout the course.
🔗 Postgraduate program official website
- Consolidate learning through hands-on projects
- Explore different areas of Artificial Intelligence
- Build a technical study portfolio
- Document experiments and learnings
Each directory represents a separate project:
.
├── project-01-name/
│ ├── README.md
│ └── project-files
│
├── project-02-name/
│ ├── README.md
│ └── project-files
│
└── ...
Each project may include:
- Problem description
- Objectives
- Technologies used
- Setup and execution instructions
- Results and learnings
- Machine Learning
- Deep Learning
- NLP (Natural Language Processing)
- Computer Vision
- LLMs and Prompt Engineering
- AI Agents
- MLOps
- AI-applied Data Science
(This list will be updated as new projects are added.)
- Choose a project folder
- Read the project's
README.md - Run the examples locally (when applicable)
Depending on the project, the following may be used:
- Python
- Jupyter Notebook
- PyTorch / TensorFlow
- Scikit-learn
- Pandas / NumPy
- LLM APIs
- LangChain / agent frameworks
- Docker
This repository is part of my continuous learning journey in Artificial Intelligence, with a focus on hands-on practice and experimentation.
Projects in this repository are for educational purposes and may evolve or be refactored over time.
⭐ Feel free to follow along with the progress!