I've worked quite a lot with C for several years, which provided me with a vision of the causal structure of sofware, from memory and time to state and failure.
C knowledge has given me strong programming fundamentals and understanding.
In C, I've worked with:
The core C language & memory model, which includes memory and data representation, pointers, parameter and function semantics, types and abstractions, scope and lineage.
The compilation model, including preprocessing, compilation, linking stages, header vs source responsibilities, symbol resolution and linker errors, and compiler warnings and optimization flags.
lex/flex, including lexical analysis, finite automata–based tokenization, compiler pipeline concepts, and generated C code integration.
I built a Lexical Analyzer you can check at the coding–projects section.
Concurrent and systems programming, including multithreading, low level I/O and OS interaction, time and execution.
OpenGL and C++, including graphics programming, human–computer interaction considerations, and CPU–GPU interfacing.
I built a Virtual Tour you can check at the coding–projects section.
Python is the language where I like to think and explore. It allows me to move fluidly from raw data to structured representations, experimenting with algorithms and dynamics that approximate reasoning rather than enforcing rigid control.
In Python, I've worked with:
Scripting, for rapidly prototyping ideas, automating experiments, and building exploratory tools where iteration speed and feedback are critical.
Object-Oriented Programming, to structure complex systems, encapsulate models and behaviors, and manage evolving codebases beyond small-scale scripts.
Jupyter Notebooks & Colab, as environments for analysis, experimentation, and communication, combining code, results, and reasoning in a single workflow.
Libraries:
NumPy, including n-dimensional array manipulation, vectorized operations, broadcasting semantics, and numerical computing workflows.
Pandas, including tabular data manipulation, indexing and filtering, data cleaning, aggregation, and exploratory data analysis workflows.
Matplotlib, including figure and axes management, custom plots, annotations, and publication-oriented visualizations.
Seaborn, including statistical data visualization, high-level plot composition, and integration with Pandas data structures.
SciPy, including use of scientific computing utilities, numerical routines, and integration with NumPy-based workflows.
scikit-learn, including use of classical machine learning models, preprocessing pipelines, model evaluation, and integration with NumPy and Pandas workflows.
Projects:
I built a Class Scheduler you can check at the projects section.
I built Stylometry Modules you can check at the projects section.
Certificates:
In Java, I developed a solid foundational understanding of object-oriented programming and software design principles, which strongly shaped how I structure and reason about larger codebases across languages.
In Java, I've worked with:
Object-Oriented Programming, including classes and objects, inheritance, polymorphism, interfaces, method overloading, and abstraction.
Data structures and algorithms, including implementation and use of common data structures and their interaction with object-oriented design.
File I/O and basic persistence, including reading from and writing to files and managing structured data input/output.
Concurrency fundamentals, including basic multithreading concepts and synchronization primitives.
Software design and modeling, including UML diagrams, design patterns, and structured program architecture.
I also took a course of basic Java by the Facultad de Ingeniería UNAM
In basic web development, I've worked with:
HTML, including writing, reading and understanding document structure, semantic elements, and adapting existing page layouts.
CSS, including modifying styles, layout rules, and visual components within existing designs.
JavaScript, including understanding and adjusting basic client-side behavior and interactions.
I built this page using simple HTML, CSS and Javascript.
In relational databases, I developed a solid foundational understanding of data modeling and structured data management through academic and practical use.
While not a current focus, this experience provided a durable conceptual foundation in relational data structures and database-backed system design.
In relational databases, I've worked with:
Relational data modeling, including entities, attributes, primary and foreign keys, and common relationship types.
SQL, including writing basic to intermediate queries for data retrieval, filtering, aggregation, and joins.
Oracle SQL, including academic and practical use of relational schemas and query-based data access.
Microsoft SQL Server, including exposure to relational database design and structured querying.
Certificates:
I've worked across different operating system environments as both development and daily-use platforms. This made me comfortable using different OS ecosystems, with their tooling, conventions and friction.
macOS, my primary development environment since 2022.
Linux, mainly Debian- and Ubuntu-based distributions, used as my primary systems between 2018 and 2022.
Windows, my main operating system prior to 2018.
Shell-based workflows, including regular use of the terminal for navigation, scripting, and development-related tasks.
Zsh, my current shell environment on macOS.
Bash, used extensively on Linux systems, with ongoing formalization through a dedicated Bash course.
x
I've worked with:
Git. x.
Github. x.
Certificates:
x
x
Visual Studio. x.
Visual Studio Code. x.
x
Microsoft Office. x.
LaTeX. x
Markdown. x
x
x:
Design Patterns. x.
MVC architecture. x.
Agile Methodologies. x.
x
Certificates: