About Me

Hello. I'm a tech enthusiast passionate about AI, Robotics, Data Science and game development. In my downtime, I delve into diverse hobbies - from immersing myself in books to strategic games of chess. Whether synthesizing digital music, working out, or honing my writing, I maintain a multifaceted skill set. Between these pursuits, I sharpen my problem-solving skills with coding challenges on platforms like HackerRank and CodinGame.

My tech passion ignited at age 12, kindled by the first Iron Man movie. Since then, maturing from unrealistic childhood aspirations of superheroism, my focus has shifted to leveraging technology for meaningful and sustainable real-world impact. I got a Bachelor's degree in Robotics at the University of Plymouth, setting the stage for my current role as an RPA developer at GTBank Uk. Simultaneously, I am immersed in a master's program in computer science, specializing in AI, at the University of Nottingham.

I thrive on tackling challenging problems which require both analytical precision and creative ingenuity. I'm eager to collaborate on projects that demand logical rigor and creative thinking to enhance the quality of human life and contribute to transformative advancements in the evolving tech landscape.

Skills (Overview)

Work Experience

Education

Python
Object oriented programming (OOP) in Python.
C++
Proficient in C++ syntax with good understanding of the fundamentals.
MySQL
Database manipulation using MySQL.
Lua
OOP and game development in Lua.

2023 - Present
RPA Development at Guaranty Trust Bank UK.

2023 - Present
MSC Computer Science (AI) at University of Nottingham.
2017 - 2020
BEng Robotics at Plymouth University.

My Skills

Python

I have nearly a year's worth of experience of programming in Python. I've collaborated with a team to develop a Rummikub variant as part of my programming coursework, implemented a genetic algorithm for string guessing, used linear regression and random forest models to analyse tiktok virality and so on. I'm familiar with core data science and machine learning libraries including numpy, pandas, matplotlib, seaborn, nltk, tensorflow and scikit-learn. And I hone my problem solving skills through the occassional practice on platforms like Hackerrank and CodingGame.

MySQL

With 3 months of hands-on experience, my proficiency in MySQL revolves around practical applications. As part of my coursework, I utilized SQL to manipulate data in a traffic incident management system, showcasing the ability to implement database concepts in real-world scenarios. Additionally, in my role as an RPA Developer, I regularly leverage MySQL queries for effective database manipulation.

C++

My focus here lies in mastering the syntax and honing strong problem-solving skills. While yet to delve into Object-Oriented Programming, my command over C++ shines in writing algoritms. Regular practice on platforms like Hackerrank and CodinGame ensures a solid understanding and proficiency in leveraging C++ for problem-solving and algorithmic challenges.

Lua

Self-taught in Lua, I've delved into Object-Oriented Programming, utilizing it to develop a game on Roblox. Regular problem-solving sessions on Hackerrank and CodinGame serve as my ongoing learning grounds to raise my proficiency in Lua.

My Projects

Simple Sentiment Analysis

For a personal project, I conducted sentiment analysis on various articles using Python. I used the Natural Language Toolkit (NLTK) library for foundational NLP tasks and TextBlob for sentiment analysis. Data preprocessing involved extracting summaries from articles to filter boilerplate content. During the analysis, I encountered challenges like library dependency issues and discrepancies between summarized and full-text sentiment scores. Exploring those discrepancies, I observed sentiment scores are likely influenced by summarization and context. I concluded that further refinement in preprocessing techniques and incorporating contextual understanding into the analysis may enhance its accuracy.

Handwritten Digit Recognition

In this projecy, I programmed a "Handwritten Digit Recognition system", drawing from Michael Nielsen's 'Neural Networks and Deep Learning.' By implementing the neural network from scratch, I explored core concepts like perceptrons, sigmoid neurons, forward and back propagation, cost function optimization and gradient descent. The neural network comprised of fully connected sigmoid neurons, including 1 hidden layer of size 20. The input layer of 784 neurons represented grayscale values in a 28 x 28 image, while the output layer was size 10 for digits 0 to 9 classification. Additionally, I replicated the network using TensorFlow and Keras libraries. Lastly, this project remains ongoing as I continue working through Michael's book which extends to deep neural networks.

Encrypted Message Decoder

As part of a self-directed project, I immersed myself in a structured course on evolutionary algorithms, focusing on developing a genetic algorithm tailored for string guessing. The algorithm comprised crucial elements, including chromosomes for the initial population, a fitness function for solution evaluation, chromosome selection to identify the most fit individuals and a random leftover sample from the population to avoid getting stuck in a local optima, chromosome crossover for reproduction, and random mutation for exploration. This project enhanced my understanding of evolutionary algorithms and sharpened my practical skills in algorithmic design and optimization.

Tiktok Analysis

For a personal project, I analyzed TikTok data, aiming to discern features correlated with increased video plays. Utilizing Apify for data scraping, I obtained a large dataset which underwent cleaning, including discarding unnecessary features and handling missing data. I Explored features such as engagement, posting day/time, video duration, music, and hashtags, employing a Random Forest model initially and also exploring Multiple Linear Regression. The models reached unsuprising conclusions on what features are more strongly correlated with video plays. And ideas for future work include refining preprocessing techniques and addressing outliers to improve model accuracy as well as exploring alternative models.

Rummikub Game-Variant

I lead a team of five students for a Rummikub Python project. My role as Team Leader involved meticulous organization, effective task distribution, and setting clear deadlines. Strategic project planning and time management ensured concurrent frontend and backend development within our three-week timeline. Comprehensive research in the early phase facilitated the smooth implementation of the game design in pygame. Conflict resolution skills addressed challenges, maintaining a positive team dynamic. My technical contributions included initialising the Gameboard class, implementing the AI player and autoplay functionality, integrating sound effects, and helping resolve various logical errors.

Team versus Game

I Undertook a six-month personal project to develop a team-versus-game on Roblox. I learnt modeling, animation and VFX (for Roblox only), and Lua programming. I coded the scripts and employed building techniques to craft a unique user experience. Applied problem-solving skills to troubleshoot technical issues, including debugging and performance optimization. Exhibited project management proficiency by setting development goals, creating timelines, and managing tasks via Trello. Showed strong commitment and work ethic by persistently dedicating time and effort to complete the.

See more on github

Hello! I'm Praise
Nnadi.

About Me

My Skills

Python

MySQL

C++

Lua