University of Utah

Master's Degree in Computer Science

Minor Degree in Cognitive Sciences

Completed Courses:

• CS3500 -Software Practice (A) +

  Software: C#, Microsoft MAUI, XAML, Visual Studio Code, Github, SQL
  Description: Practical exposure to the process of creating large software systems, including requirements specifications, design, implementation, testing, and maintenance. Emphasis on software process, software tools, software engineering techniques, and team development practice. Much of the work will be in groups and will involve modifying preexisting software systems.

  Skills: SOLID code principles, Git, Logging, Web Servers and Networking, SQL databases, JSON serialization .

• CS2420 - Data Structures and Algorithms (A) +

  Software: JavaScript, Eclipse
  Description: This course provides an introduction to the problem of engineering computational efficiency into programs. Students will learn about classical algorithms (including sorting, searching, and graph traversal), data structures (including stacks, queues, linked lists, trees, hash tables, and graphs), and analysis of program space and time requirements. Students will complete extensive programming exercises that require the application of elementary techniques from software engineering.

• CS3810 - Computer Organization (B+) +

  Software: Mars Simulator, MIPS Assembly
  Description: An in-depth study of computer architecture and design, including topics such as RISC and CISC instruction set architectures, CPU organizations, pipelining, memory systems, input/output, and parallel machines. Emphasis is placed on performance measures and compilation issues.

• CS2100 - Discrete Structures (A) +

  Description: Introduction to propositional logic, predicate logic, formal logical arguments, finite sets, functions, relations, inductive proofs, recurrence relations, graphs, probability, and their applications to Computer Science.

• CS1410 - Object-Oriented Programming (A) +

  Software: Javascript, Eclipse, Python, Pycharm
  Description: This course explores foundational programming skills while introducing the paradigm of object-oriented programming.

• CS4150 - Algorithms +

  Study of algorithms, data structures, and complexity analysis beyond the introductory treatment from CS 2420. Balanced trees, heaps, hash tables, string matching, graph algorithms, external sorting and searching. Dynamic programming, exhaustive search. Space and time complexity, derivation and solution of recurrence relations, complexity hierarchies, reducibility, NP completeness. Laboratory practice.

• CS3505 - Software Practice II +

  An in-depth study of traditional software development (using UML) from inception through implementation. The entire class is team-based, and will include a project that uses an agile process. All assignments for this course are coded in C++ and the final two assignments for this course use QTCreator to create an interactive UI.

• CS3520 - Programming Languages Concepts +

  Ideas behind the design and implementation of programming languages. Syntactic description; grammars and abstract syntax; interpreters and compilers; scope and lifetime of variables; order of evaluation; continuation representation; type systems.

• CS3190 - Found. Of Data Analysis +

  This class will be an introduction to computational data analysis, focusing on the mathematical foundations. The goal will be to carefully develop and explore several core topics that form the backbone of modern data analysis topics, including Machine Learning, Data Mining, Artificial Intelligence, and Visualization. This will include some background in probability and linear algebra, and then various topics including Bayes' rule and connection to inference, gradient descent, linear regression and its polynomial and high dimensional extensions, principal component analysis and dimensionality reduction, as well as classification and clustering. We will also focus on modern models like PAC (probably approximately correct) and cross-validation for algorithm evaluation.

In Progress:

• CS4530 - Mobile Application Programming +

  Software: Android Studio, Java, Kotlin, SQLite
  Description: An introduction to the theory and practice of application development for mobile phones and tablets, including a focus on general program organizational techniques. Topics include native language foundations, automatic UI layout techniques, custom views and controls, data persistence, data driven user interfaces, application lifecycle, application architectural models like Model-View-Adapter, internet service interaction, RESTful web services, and 2D OpenGL rendering. Students will complete several programming projects during the course to explore these topics. A final project of the student's own design will make up a large part of the class.

• CS5530 - Database Systems +

  Software: MySql, Putty
  Description: This course is designed to cover the fundamental database concepts and query languages that are used in current relational database engines. A large portion of the course will consist of a multi-phase project throughout the semester, in which students will implement a learning management system (LMS) like Canvas.

• DS2500 - Data Wrangling +

  Software: Google Colab, Python
  Description: The course will introduce students to basic techniques in collecting, scrapping, transforming, and normalizing data, as a first step in a data science pipeline. Students will learn by working with a variety of standard data processing tools, and experimenting on numerous example tasks.

Expected Graduation: Fall 2027 | GPA: 3.8