Data Analytics: Proficient in Python, SQL, R, NumPy, Pandas, Excel (pivots, lookups), Power BI in performing data analytics and statistical computations. Three years of experience in Python and R working with probability models and statistical computations.
Programming: Three years of experience in programming languages; Python, C, Bash/Linux, R, C++
• Contributed to AI team on the design, testing and refinement of machine learning models for voice synthesis technology
• Assisting in the analysis and processing large data sets for AI model training and resolving issues during testing phases
• Supporting the evaluation and implementation of new coding techniques and technologies to enhance AI solution
• Documenting development processes and findings in a clear and concise manner
• Demonstrated professionalism and excellent communication skills through one-on-one sessions by contributing approximately two hours per week to solidify student’s understanding regarding grade eleven math contents with detailed explanations.
• Provided clear and constructive feedback to the student during each tutorial session highlighting her strengths and the areas of improvement, resulting in over twenty percent rise in the student’s mark in class
Personal Finance Automation 11/2023 – 01/2024
Project Summary: An analysis program that helps users to manage and gain an overview of their spending trends.
• Used csv files from bank summary and Python libraries such as NumPy, Pandas, Matplotlib and relevant others to plot graphs to visualize the spending trend and use of linear regression line to effectively manage future spendings.
• Conducted data cleaning in csv file such as removing NaN values that may disrupt graphing and computations and renaming columns for clarification of the type of all values.
• Assisted users to visualize their spendings
Chess Game in C++ (Group Final Project) 11/2023 - 12/2023
Project Summary: An interactive chess game for human and computer players of different levels
• Developed an interactive C++ OOP-based chess program developed by three people, featuring human-computer interactive game modes. Employed the observer design pattern to update moves on the board and offers four levels of computer intelligence; the most advanced AI can predict and evaluate up to three opponent moves ahead, choosing the optimal strategy.
• Took into consideration specific rules such as en passant, pawn upgrade, and castling.
• Received a 94.2% project evaluation score.