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Greetings πŸ‘‹ from La Wun Nannda

An Undergraduate Exploring Different Fields of CS

Introduction

  • 🌱 I’m currently learning Machine Learning, Quantum Computing, DSA, and Computer Science
  • πŸ‘― I’m looking to collaborate on projects related to Data and Humanitarian Issues
  • πŸ€” I’m looking for help with understanding DSA and SWE concepts
  • πŸ’¬ Ask me about Arduino and Python
  • πŸ“« How to reach me: [email protected]
  • ⚑ Fun fact: I like Emojicode, a programming language in emojis

My Background

  • With my team, I created a bluetooth-controlled car for the project show on my first academic year.
  • I built several fun projects on my own, using the Arduino platform: smart home, IoT temperature control, door lock system, plant monitoring system, etc.
  • With my team, I built the Refiller Robot using the Arduino platform for COVID-19 era, which was later donated to Wai Bar Gi Hospital, Myanmar. We were from the Laboratory of Robotics and Artificial Intelligence (LORA) of Yangon Technological University. The project was interviewed by the BBC News Myanmar.
  • I jumped from Arduino to Python because of my passion in coding in 2020.
  • Since them, I have been exploring several different fields of Computer Science: from Octave and Machine Learning, to Data Science and Quantum Algorithms.
  • I attended the UoPeople in 2022 to become a CS undergrad.
  • I love to get a career that involves helping people with what I know.

What I know

Most-used Languages & Libraries:

Exposed Languages & Libraries:

Tools:

My Status

Connect Me

La Wun Nannda's Projects

classiq-library icon classiq-library

The Classiq Library is the largest collection of quantum algorithms, applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library πŸ™Œ

dev-house icon dev-house

Developers from Myanmar and build Dev-House on Internet :)

eliza icon eliza

A Simulation in C++ of Joseph Weizenbaum’s 1966 ELIZA

llm-datasets icon llm-datasets

High-quality datasets, tools, and concepts for LLM fine-tuning.

ostep-code icon ostep-code

Code from various chapters in OSTEP (http://www.ostep.org)

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