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.

Vector Calculus In this course students will apply the concepts and tools of linear algebra to analyze functions of multiple variables where domain and codomains are vectors, possibly of different dimensions.  Students will learn introductory vector analysis, partial differentiation, multiple integration, line integrals, elementary vector field theory, and their applications.

Breaking the Code: The Enigma of Alan Turing British mathematician Alan Turing broke the German military’s prized Enigma cipher in World War II, created the foundations of modern computer science, and pioneered the fields of artificial intelligence (“Can Machines Think?”). Turing was arrested for homosexuality and forced to undergo hormone treatments which may have led to his apparent suicide by cyanide poisoning. His brilliant achievements and tragic death have been the subject of biographies, essays, plays, novels, and films. In this course we will explore the life, times, and works of this remarkable individual and consider how Turing would view the current state of artificial intelligence.

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)

Multivariable Calculus The calculus of functions of more than one variable. Introductory vector analysis, analytic geometry of three dimensions, partial differentiation, multiple integration, line integrals, elementary vector field theory, and applications.

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.

Mathematical modeling An introduction into the process of developing and interpreting mathematical models within the framework of numerous applications. In this course, we will utilize discrete, continuous, and probabilistic approaches to explore applications such as population dynamics, epidemiology, and neuron activity.  Time permitting, we may also introduce the derivation of spatiotemporal models.  MATLAB will be used to implement and analyze several of these models.

Elementary Topology An introduction to the concepts of topology. Theory of sets, general topological spaces, topology of the real line, continuous functions and homomorphisms, compactness, connectedness, metric spaces, selected topics from the topology of Euclidean spaces including the Jordan curve theorem. (MATH 0122 or MATH 0200 or by waiver)

Operations Research Operations research is the utilization of quantitative methods as an aid to managerial decisions. In the course, several of these methods will be introduced and studied in both a mathematical context and a physical context. Topics included will be selected from the following: classification of problems and the formulation of models, linear programming, network optimization, transportation problems, assignment problems, integer programming, nonlinear programming, inventory theory, and game theory.

Advanced Mathematical Modeling Seminar A tutorial on advanced mathematical model building and analysis for students who have completed work in Differential Equations and Probability. We will study deterministic and stochastic models of interacting populations with a focus on mathematical ecology and epidemiology. Working independently and in small groups, students will gain experience reading advanced sources and communicating their insights in expository writing and oral presentations. Fulfills the capstone senior work requirement for the mathematics major. (Approval Only) 3 hrs. Sem.

Mike Olinick

Reviews and ratings for Mike Olinick at Middlebury College.Mike Olinick teaches Linear Algebra, Vector Calculus, Breaking the Code: Alan Turing and more.  Explore top rated instructors and find the best for you.Is Mike Olinick good ? Find out on MiddCourses.

This was a very interesting course, and a lot of the things learned here would prove to be useful in future Math courses. Also, the work and projects allowed you to apply these concepts to real-life scenarios, which I thought was pretty cool. Not too hard and pretty rewarding.

Olinick is clearly passionate about the material, but the lectures were extremely boring and unrelated to the homework or exams. The exams weren’t particularly hard, but they required you learn the content on your own.

I self-studied for most of his exams, but that was primarily because I thought the way he taught was pretty uninteresting. I think he tends to teach a little slow-paced, and it doesn't help that his voice is pretty easy to zone out to. I would say this course is really good in terms of content, super important to understand for later concepts, but don't think you should take it with him.