Applied Mathematics Research Topics: Linear Algebra, Calculus And Algorithm Model Errors

Course Arrangement

Enrollment status: Enrolling

Course time: rolling classes

Course method: Zoom remote live teaching

Course schedule: 21 class hours for the main academic tutor + 9 class hours for the academic associate tutor + 6 class hours for the main thesis tutor + 21 class hours for the deputy thesis tutor, lasting 7 weeks

Course Description

Numerical analysis is a discipline that studies and analyzes numerical calculation methods and theories of using computers to solve mathematical calculation problems. It covers a wide range of fields, and the optimization problems included in it can usually be expressed as problems in the form of mathematical programming. Linear programming is an important branch of operations research that has been studied earlier, developed faster, is widely used, and has more mature methods. It is a mathematical method that assists people in scientific management and studies the extreme value problem of linear objective functions under linear constraints. mathematical theories and methods. Linear programming is widely used in military operations, economic analysis, business management, and engineering technology to provide scientific basis for rationally utilizing limited human, material, financial and other resources to make optimal decisions.

Suitable For

High school students and undergraduates interested in mathematics, linear algebra, linear programming, operations research, and computer science.

Students majoring in mathematics and wishing to engage in quantitative trading, mathematical research, operations research, computer science and other fields in the future.

Students with basic knowledge of calculus and linear algebra are preferred.

Professor Introduction

Tenured professor at the University of California, Berkeley

Ming Gu

Tenured Professor of Mathematics, University of California, Berkeley

PhD in Computer Science from Yale University

Research directions: applied mathematics , numerical linear algebra, scientific computing

Paper published at the 2017 International Conference on Machine Learning

2017 Hipc Best Paper Award

TA Introduction

Education background

Master’s/PhD background from TOP30 prestigious universities at home and abroad, over 40% of the team’s PhD students are

Professional and excellent

Have experience in publishing papers in relevant professional fields


Excellent academic performance & fluent in English, with many years of experience as a teaching assistant

teaching orientation

Seamlessly connect professor topics and participate in teaching and delivery throughout the process

Program Advantages

Complete course hours that meet the academic program requirements of colleges and universities

A complete scientific research project under the personal guidance of the professor

A true and valid recommendation letter personally issued by the professor

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