Side Projects

Here is the side project page. You will find there projects I have worked on in my free time.

Tank war

The Tank Game is a side project I decided to do to gain proficiency in Unity, while creating an interactive and enjoyable gaming experience. Tank war is a locally playable game designed for pairs.

I took charge of every aspect of its creation. This included generating and refining creative concepts, integrating gameplay mechanics, and crafting diverse maps.

As mentioned above, this project was developed with Unity, and was implemented using the C# programming language.

Through the Tank Game project, I improved my skills in Unity and c#.

Sand box

Sandbox is a project I decided to do to explore some specific concepts with Unity and also build some standalone bricks for future projects.

I discovered useful libraries and features such as ProBuilder or the built-in terrain system. I also build my own features, such as a basic first- and third-person controller or a basic inventory system. My goal was to have a base for future projects and to be able to iterate and test faster.

With this project, I learned and explored new aspects of Unity while creating a fun environment.

Planet coaster

Planet coaster is a project I started recently. The final goal is to create a solar system simulation.

The current status allows me to create a planet shape by using perlin noise to generate the terrain. I am currently working on implementing the simulation process.

Game of Life

The Game of Life project involved the implementation of Conway's Game of Life using Python and the Tkinter library to create an engaging and interactive simulation. The objective was to bring the classic cellular automaton to life, allowing users to explore the fascinating emergent patterns that arise from simple rules.
In this project I had to manage the implementation of the user interface and the development of the core functions and rules governing the Game of Life simulation. This included determining the state transitions of cells based on their neighbors and updating the grid accordingly. The implementation ensured that the simulation ran smoothly and accurately reflected the evolution of the cellular automaton over generations.