Aug 2021 – May 2025 • College Park, MD
This document lists all courses taken by the student
General Chemistry for Engineers — Fundamental chemistry for engineering, covering atomic structure, bonding, and thermodynamics.
Object-Oriented Programming I — Introduction to computer science and programming using Java.
Introduction to Engineering Design — Team-based project course focused on solving engineering problems.
Introduction to Student Leadership — Leadership theory and practice with emphasis on social change.
Calculus I — Limits, derivatives, and applications like optimization and motion.
Object-Oriented Programming II — Data structures and algorithms using Java: trees, lists, recursion.
Intro to EE & Computer Engineering — Survey of ECE disciplines, including hardware/software fundamentals.
Equity & Inclusion in Engineering Design — Exploration of equity and inclusive practices in design.
Academic Writing — Foundational college writing, rhetoric, and argumentation.
Calculus II — Integration techniques, sequences, series, and applications.
Mechanics and Particle Dynamics — Newtonian mechanics and motion in one and two dimensions.
Digital Logic Design — Boolean logic, combinational/sequential circuits, finite state machines.
Calculus III — Multivariable calculus: partial derivatives, gradients, and multiple integrals.
Tenor & Bass Choir — Performance and rehearsal for tenor/bass vocal ensemble.
Waves, Heat, Electricity — Physics covering wave motion, thermodynamics, electricity.
Lab for PHYS260 — Experimental reinforcement of topics in PHYS260.
Discrete Structures — Mathematical foundations for CS: logic, proofs, sets, relations.
Engineering Ethics — Ethical reasoning for engineers, addressing moral dilemmas and impact.
Electric Circuits — Principles of DC/AC circuits, impedance, and circuit analysis.
Differential Equations — First/second-order ODEs, applications to mechanical/electrical systems.
Intro to Computer Systems — C programming, memory, pointers, and OS interaction.
Organization of Programming Languages — Functional, logic, and imperative programming paradigms.
Algorithms — Algorithm design, complexity, recursion, sorting, and graph algorithms.
Discrete Signal Analysis — Discrete-time signals/systems, transforms, and sampling.
Digital Circuits Lab — Hands-on design and testing of logic circuits.
Art of Communication — Fundamentals of public speaking and performance.
Human Development & Social Institutions — Lifespan development and sociocultural influences.
Signal & System Theory — Convolution, Fourier analysis, system properties.
Computer Organization — Assembly language, datapaths, control logic, and memory.
Make Better Decisions — Behavioral economics and cognitive biases in decision-making.
Linear Algebra for Scientists and Engineers — Matrices, eigenvalues, linear systems.
Applied Probability and Statistics I (Retake) — Improved mastery of foundational stats topics.
Co-op Internship — Non-credit cooperative work experience in engineering field.
Introduction to Artificial Intelligence — Search, reasoning, decision-making, and ML basics.
Foundations of Machine Learning — Theory and applications of supervised and unsupervised learning.
Microprocessors — Assembly, interrupts, embedded systems with microcontrollers.
Digital Computer Design — CPU architecture, datapath, pipelining, control units.
Technical Writing — Writing and documentation for technical and scientific contexts.
The Coding Interview — Algorithms, problem-solving, and mock interviews.
Design Experience: Machine Learning — Capstone focused on ML systems and deployment.
Operating Systems — Process management, scheduling, memory, file systems.
Control Systems Laboratory — Design, implementation, and tuning of control systems.
Advanced Entrepreneurial Opportunity Analysis — Business models, startup execution, innovation.
Literature in Journalism — Literary analysis of nonfiction narrative and journalistic texts.
Introduction to Artificial Intelligence — Search, reasoning, decision-making, and ML basics.
Foundations of Machine Learning — Theory and applications of supervised and unsupervised learning.
Microprocessors — Assembly, interrupts, embedded systems with microcontrollers.
Digital Computer Design — CPU architecture, datapath, pipelining, control units.
Technical Writing — Writing and documentation for technical and scientific contexts.
The Coding Interview — Algorithms, problem-solving, and mock interviews.
Design Experience: Machine Learning — Capstone focused on ML systems and deployment.
Operating Systems — Process management, scheduling, memory, file systems.
Control Systems Laboratory — Design, implementation, and tuning of control systems.
Advanced Entrepreneurial Opportunity Analysis — Business models, startup execution, innovation.
Literature in Journalism — Literary analysis of nonfiction narrative and journalistic texts.