Spring 2020,
Prof. Jae Lee
"Right now, you are a programming student. After this course, you will become a programmer." Taught the basics of C, C++, command line tools, and advanced techniques & design principles. Specifically, it explored Makefile, binaries, pointers & arrays, function pointers, structs, unix commands, fork & exec, TCP/IP/HTTP, Endianness, Sockets, templates & STL in C++, and Smart Pointer.
Spring 2020,
Prof. Yannakakis
Per course syllabus: One goal of the course is to present the fundamental models of computation, their properties, and methods for analyzing them. The second goal is to address the central questions of computability (which problems can be solved by a computer?) and complexity (which problems can be solved in reasonable amounts of time and memory?). Specific topics to be covered include: Finite automata and regular expressions, Context-free grammars, pushdown automata, Turing machines, decidability, reductions, and Complexity classes: P, NP, NP-completeness
Spring 2020,
Prof. Sethumadhavan
Per course syllabus (Prof. Kim's): The purpose of this course is to examine how the digital 1s and 0s that are the foundation of digital computing are organized, structured, and manipulated to become a full-fledged computer system. In bridging this gap, the course will cover many subjects beginning with binary logic, combinatorial and sequential circuit design, memory structures, instruction set architectures, and, ultimately, basic processor design.
Spring 2020,
Prof. Vallancourt
This course taught concepts of electronic systems. Specifically, we learned about opamps: feedback, ideal opamps, finite open loop gain, effects of DC gain, frequency response, slew rate, current limits, input bias and offset current, CMRR, integrators. Diodes: shockley equation (YES!!!), bandgap reference, diode large signal & small signal models, clippers, rectifiers, diode currents, zeners, load line analysis. MOS Transistor topics: NMOS, PMOS, linear, triode, saturation, low frequency common-source, degeneration, etc. Bipolar transistors.
Fall 2019,
Prof. Bauer
I took this course again at Columbia to cement my education in Data Structures, Graphs, ADTs, and algorithms.
Fall 2019,
Prof. Tsividis
Learned more about op-amps and other electrical engineering components as well as laws.
Fall 2019,
Prof. Wang
Introduction into signals and systems, fourier series for periodic signals, fourier transforms and frequency-domain analysis, Laplace transofrm and system analysis, and introduction to discrete-time signals and systems.
Fall 2019,
Prof. Lacker
"Teaches foundations required to use probability in applications, but the course itself is theoretical in nature. Basic definitions and axioms of probability and notions of independence and conditional probability introduced. Focus on random variables, both continuous and discrete, and covers topics of expectation, variance, conditional distributions, conditional expectation and variance, and moment generating functions. Also Central Limit Theorem for sums of random variables. Consists of lectures, recitations, weekly homework, and in-class exams."
-Course Syllabus
Pittsburgh, PA
JamesMastran@gmail.com
MastranJ@jay.washjeff.edu
Jam2454@columbia.edu
Mobile: (+1) 412 877 0484