The majority of my graduate studies was spent on modelling mathematical problems involving PDEs and ODEs using numerical methods. Taugh freshman engineering students how to model Calculus I-II problems using Python's Math, SymPy & NumPy libraries.
Exploratory Data Analysis
Analyzed various datasets using R during Ph.D.-level Statistics courses: Regressional Analysis, Time Series Analysis, as well as Applied Biostatistics & Data Analysis @ TAMU. Spent most of my spare time working on various datasets in Kaggle and deploying Machine Learning models using Python.
Machine & Deep Learning
Completed Coursera's Machine Learning course (by Stanford University) and Deep Learning Specialization (by deeplearning.ai), as well as Udemy's Python for Data Science and Machine Learning Bootcamp. Finished 13/15 mini-courses in Kaggle, and in progress with Coursera's Applied Machine Learning with Python course (by UMICH).
Taught Calculus I-II classes using Python. Wrote most of the Data Science / ML / DL and Algorithms codes in Python. Highly experienced in Jupyter Notebook, Google Colab & Visual Studio Code platforms. Worked on SciPy environment (SymPy, NumPy, Pandas, matplotlib etc.), scikit-learn, Tensorflow 2.0 & Keras. I enjoy challenging myself on programming problems @ EulerProject, HackerRank, and LeetCode.
Used R Studio and R markdown for multiple Ph.D.-level Statistics courses for regression, time series, and data analysis.
Used SQL for data wrangling and management during Ph.D.-level Statistics course - Databases and Computational Tools Used in Big Data. Learned writing basic to advanced SQL queries using google.cloud library in Python from Kaggle, and MySQL from Udemy.
Taught Calculus classes in MATLAB. Most of the projects and homework in graduate studies were written in MATLAB language. Experienced with more than 10,000 lines of code, mostly for numerical analysis and computational mathematics.
Familiar with basic C/C++ programming. Used it for compiler optimization, vectorization and profiling problems during Ph.D.-level Statistics course - Databases and Computational Tools Used in Big Data.