Richard Ahn
  • Home
  • Contact
  • Courses
  • Projects
    • Hack112
    • 15-112 Term Project
    • Restaurant Webpage
    • SportsStats
    • Titanic ML
    • TartanHacks 2023
    • Football ML
    • See You Later Hackulator
  • Experience
Richard Ahn
  • Home
  • Contact
  • Courses
  • Projects
    • Hack112
    • 15-112 Term Project
    • Restaurant Webpage
    • SportsStats
    • Titanic ML
    • TartanHacks 2023
    • Football ML
    • See You Later Hackulator
  • Experience

Classes

Below are all of my classes I have completed in relation to my professional growth in the tech industry. My expected graduation date is May 2025

Fundamentals of Programming and Computer Science

15-112

Course Description

  • Learning the principles of Python along with an emphasis on producing clear, robust, and efficient code with proper design and practice

Principles of Imperative Computation

15-122

Course Description

  • Covers imperative programming with C and also covering data structures and algorithms along with fundamental concepts like abstraction, correctness, complexity, modularity

Probability and Statistical Inference I

36-235

Course Description

  • Covers theoretical aspects of probability and statistical inference covering basic probability, random variables, univariate probability distribution functions, point and interval estimation, hypothesis-testing, and regression
  • Focuses on integrating data and concepts through R

Probability and Statistical Inference II

36-236

Course Description

  • Binomial, Poisson, and uniform probability distributions
    • How they are used in the context of making point estimates, constructing confidence intervals, and performing hypothesis tests
    • Covering generalized linear models as well as concepts related to multivariate distributions: marginal and conditional distributions, covariance and correlation, and conditional expected values and the law of total probability
    • Focuses on integrating data and concepts through R

Statistical Computing

36-350

Course Description

  • Computational Data Analysis course
  • Data structures, functions, iteration, debugging, logical design, and abstraction 
  • Taught in R and SQL

Modern Regression

36-401

Course Description

  • Advanced statistics course
  • Applied data analysis, modeling tools and techniques, and advanced topics and assumption examination
  • Also teaches R 

Concepts of Mathematics

21-127

Course Description

  • Focuses on mathematical reasoning and building proofs and observe how sophisticated counting techniques help with mathematics

Integration and Approximation

21-122

Course Description

  • Focuses on differentiation and integration as well as approximation and continuing upon building integration-related knowledge

Matrices

21-240

Course Description

  • Covering linear algebra concepts involving matrices, linear independence, eigenvetors and eigenvalues, and more

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