Kanishk Kacholia

Studying at The University of Minnesota Twin Cities

🎓 Majoring in Computer Science, Data Science, and a minoring in GIS and Business Management

Last updated: May 27th, 2023

University of Minnesota Twin Cities

Fall 2021 - Present

I am currently a honors student at the University of Minnesota - Twin Cities pursuing majors in Computer Science and Data Science with minors in Geographic Information Systems and Business Management.

    algorithms & data structurescomputational linear algebramachine architecture

Current Degree Progress 62.5%

Fall 2023

Optimization for Machine Learning

This course introduces some fundamental solution methods for solving various optimization models arising in the context of machine learning in areas such as computer vision, search engines, speech recognition, robotics, recommendation systems, bioinformatics, social networks, and finance.

Spring 2023

Program Design and Development

Principles of programming design/analysis. Concepts in software development. Uses a programming project to illustrate key ideas in program design/development, data structures, debugging, files, I/O, testing, and coding standards.

Fall 2022

Algorithms and Data Structures

    algorithms & data structures

In this class I was introduced to more complex and dynamic data structures within Computer Science and the theory behind them. Some noteable examples include minheaps, graphs, greedy algorithms, graph navigation algorithms, and dynamic programming.

Spring 2022

Elementary Computational Linear Algebra

    computational linear algebra

The primary purpose of this course was to teach the basics of Linear algebra with a focus on how it relates to Computer Science topics. Topic examples include vector spaces, linear equations, eigenvalues, regression development using matrix projections.

Fall 2021

Introduction to Algorithms, Data Structures, and Program Development

    javaalgorithms & data structures

A Java based development course that focused on implementing basic data structures found in Computer Science. These included stacks, queues, linked lists, binary lists, and hash tables. In addition we focused on sorting algorithms and runtimes.