Linear Algebra Matrices and systems of linear equations, the Euclidean space of three dimensions and other real vector spaces, independence and dimensions, scalar products and orthogonality, linear transformations and matrix representations, eigenvalues and similarity, determinants, the inverse of a matrix and Cramer's rule.

Advanced Numerical Analysis In this course, students will complete a senior project building on their prior knowledge and experience in numerical methods and analysis. Each iteration of the course may highlight different areas and applications of numerical analysis, shaped by the instructor’s expertise and areas of interest. Students will develop their ability to critically analyze, synthesize, and engage in meaningful discussions about relevant scientific literature. Emphasis is placed on clear written and oral communication of mathematical ideas, culminating in a formal scientific paper and a public presentation. This course fulfills the capstone senior work requirement for both the applied and general mathematics tracks. (Approval Only) 3 hrs. Sem.

Calculus II A continuation of MATH 0121, may be elected by first-year students who have had an introduction to analytic geometry and calculus in secondary school. Topics include a brief review of natural logarithm and exponential functions, calculus of the elementary transcendental functions, techniques of integration, improper integrals, applications of integrals including problems of finding volumes, infinite series and Taylor's theorem, polar coordinates, ordinary differential equations. MATH 0121 or equivalent, or by placement)

Numerical Linear Algebra Numerical Linear Algebra involves the development, analysis, and implementation of computational algorithms for solving linear algebra problems. These problems frequently arise in applications such as physical simulations, signal processing, neural network design, and many more. This course focuses on numerical methods for linear systems and eigenvalue problems. We will study both direct and iterative approaches, including Gaussian Elimination, LU Factorization, Jacobi and Gauss-Seidel Iterations, Steepest Descent, Conjugate Gradient, the Power Method, and more.  Additional key topics include matrix decompositions, matrix/vector norms, computational efficiency, and stability. MATLAB programming skills will be introduced and developed throughout the semester.

Differential Equations This course provides an introduction into ordinary differential equations (ODEs) with an emphasis on linear and nonlinear systems using analytical, qualitative, and numerical techniques.  Topics will include separation of variables, integrating factors, eigenvalue method, linearization, bifurcation theory, and numerous applications.  In this course, we will introduce MATLAB programming skills and develop them through the semester.

Partial Differential Equations An introduction to partial differential equations (PDEs) with an emphasis on first and second-order  linear equations. Using analytical, qualitative, and numerical techniques, we will study the Laplace,  heat, and wave equations, as well as their applications. MATLAB will be used where applicable.  (MATH  0223 and either of MATH 0225 or MATH 0226) 3 hr lect.

Calculus I Introductory analytic geometry and calculus. Topics include limits, continuity, differential calculus of algebraic and trigonometric functions with applications to curve sketching, optimization problems and related rates, the indefinite and definite integral, area under a curve, and the fundamental theorem of calculus. Inverse functions and the logarithmic and exponential functions are also introduced along with applications to exponential growth and decay.

Introduction to Numerical Analysis We will study the development, analysis, and implementation of numerical methods for approximating solutions to mathematical problems. We will begin with applications of Taylor polynomials, computer representation of numbers, and types of errors.  Other topics will include polynomial and spline interpolation, numerical integration and differentiation, rootfinding, and numerical solutions of differential equations.  Accuracy will be quantified by the concept of numerical error.  Additionally, we will study the stability, efficiency, and implementation of algorithms.  We will utilize the software MATLAB throughout to demonstrate concepts, as well as to complete assignments and projects.

Michaela Kubacki

Reviews and ratings for Michaela Kubacki at Middlebury College.Michaela Kubacki teaches Linear Algebra, Advanced Numerical Analysis, Calculus II and more.  Explore top rated instructors and find the best for you.Is Michaela Kubacki good ? Find out on MiddCourses.

IF YOU TAKEN THE MATH AAHL international baccalaureate BEFORE, THE COURSE LEVEL IS PRETTY EASY. I WILL SAY THAT THIS CLASS DEMANDS A BUNCH OF TIME DEDICATED TO HOMEWORKS. THERE ARE ALSO A DECENT AMOUNT OF QUIZZES AND MIDTERMS. OVERALL IF YOU'RE NOT SCARED OF SPENDING TIME ON THIS SUBJECT. THE COURSE ISN'T THAT HARD. 

Professor Kubacki is a good professor who helps students with the material during office hours, she is very nice. But she moves pretty fast and sometimes doesn’t wait to explain during class if concepts aren’t understood. Generally an effective teacher and is passionate

Prof. K is amazing! She is truly passionate about teaching and explains everything in great detail, with plenty of helpful notes and board work. The workload is definitely heavy, but the homework problems are carefully selected and highly relevant to the exams. Although there are three exams, Prof. K allows us to bring two sheets of notes, which makes them very manageable. Highly recommend taking her class!