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Hi ๐Ÿ‘‹, I'm Adrian

I am a software engineer with a background in Engineering Management. I love solving problems, taking on challenges and learning new things to build projects that are exciting! I also love getting outdoors, travelling and playing sports.

  • ๐Ÿ”ญ Iโ€™m currently working on deploying full-stack web apps with Python, Vue and MySQL.

  • ๐ŸŒฑ Iโ€™m currently learning DevOps and automating CI/CD pipelines with GitHub Actions

Connect with me:

adrian-montagu

Languages and Tools:

bootstrap flask git javascript mysql python sqlite vuejs

Adrian Montagu's Projects

automated_coffee_machine icon automated_coffee_machine

Following Angela Yu's 100 days of code - these files simulates buying coffee from a machine. The machine will calculate change, store money as well as deplete in resources. The user has the option to buy coffee, refill the machine or get a report of the machine contents.

blackjack-oop-gui icon blackjack-oop-gui

First attempt using a GUI and programming using OOP principles. Created a one player game of blackjack where the player can bet money.

coding-time-keeper icon coding-time-keeper

This app allows users to track how many days and hours they have coded. It is made with beginners just starting out to code in mind.

iqarus-challenge icon iqarus-challenge

Response to Inversity Challenge - "Code Red: can technology improve the medical response to a humanitarian crisis?"

market-research-challenge icon market-research-challenge

Response to Inversity Challenge - โ€˜Reimagining Market Research. How can technology help us work out what people are thinking and turn these insights into action?โ€™

microblog icon microblog

The microblogging application developed in my Flask Mega-Tutorial series. This version maps to the 2024 Edition of the tutorial.

name-card-template icon name-card-template

Just a fun little profile/card-style template. Minimal, responsive, and powered by Skel + Sass.

q-learning-experiments icon q-learning-experiments

An implementation of Q-learning with a "gridworld" environment. An agent is embedded in a grid, and through Q-learning it learns to find its way to a goal. A PyGame animation is included to generate before-learning and after-learning comparisons of the agent's behaviour.

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