Coursework

This repository comprises my coding projects from various courses in Earth, Atmospheric, and Planetary Science (EAPS), Mathematics, and Computer Science (CS) at Purdue University. The collection includes code written in R, Python, and MATLAB. Some courses involved extensive coding tasks, while others provided pre-existing code that required cleaning and data interpretation. Each folder contains an individual README detailing the contents. Below are brief summaries of my experiences and accomplishments in each course.

EAPS 227: Introduction to Atmospheric Observations and Measurements

• Throughout this course, we learned principal techniques and instruments used in atmospheric science. We learned what they were used for, their pros and cons, and how to use them. Moreover, we used these instruments, along with python programming and statistical analysis, to carry out a final project along with a report
• Our main learning was through class lectures, using the instruments in the field, and through MetEd
• Conducted group and independent field work
• We realeased a radiosonde in class video!

EAPS 431: Synoptic Lab 1 and EAPS 520: Theory of Climate

• Used Python with weather data to determine properties of the atmosphere

CS177: Python Programming

• Learned the basics of Python. We were also introduced to basic matplotlib usage

STAT350: Introduction To Statistics

• This was a data-centered introduction covering the core concepts and methods of applied statistics. It included exploratory data analysis, sample design, and experimental design. We delved into probability distributions and simulation techniques, as well as sampling distributions. The rationale behind statistical inference was discussed, along with constructing confidence intervals and conducting tests for one and two samples. We explored inferential analysis for contingency tables, regression, and correlation. Additionally, an introduction was provided to regression with several explanatory variables, with a strong emphasis on utilizing statistical software throughout.

MA266: Differential Equations

• From the course overview page: First order equations, second and n'th order linear equations, series solutions, solution by Laplace transform, systems of linear equations. We essentiall used MATLAB to determine the answers to problems and used some light MATLAB code.