Courses tagged with "Customer Service Certification Program" (208)

This is the first semester of a one year graduate course in number theory covering standard topics in algebraic and analytic number theory. At various points in the course, we will make reference to material from other branches of mathematics, including topology, complex analysis, representation theory, and algebraic geometry.

This graduate-level course is an advanced introduction to applications and theory of numerical methods for solution of differential equations. In particular, the course focuses on physically-arising partial differential equations, with emphasis on the fundamental ideas underlying various methods.

This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language, a free, open-source, high-performance dynamic programming language for technical computing.

This course covers mathematical topics in algebra and trigonometry and is designed to prepare students to enroll for a first semester course in single variable calculus.

Curso diseñado para facilitar la entrada del estudiante en los cursos de cálculo de primer semestre de prácticamente cualquier grado universitario, con especial énfasis en Ciencias e Ingeniería.

Non-trigonometry pre-calculus topics. Solid understanding of all of the topics in the "Algebra" playlist should make this playlist pretty digestible. Introduction to Limits (HD). Introduction to Limits. Limit Examples (part 1). Limit Examples (part 2). Limit Examples (part3). Limit Examples w/ brain malfunction on first prob (part 4). Squeeze Theorem. Proof: lim (sin x)/x. More Limits. Sequences and Series (part 1). Sequences and series (part 2). Permutations. Combinations. Binomial Theorem (part 1). Binomial Theorem (part 2). Binomial Theorem (part 3). Introduction to interest. Interest (part 2). Introduction to compound interest and e. Compound Interest and e (part 2). Compound Interest and e (part 3). Compound Interest and e (part 4). Exponential Growth. Polar Coordinates 1. Polar Coordinates 2. Polar Coordinates 3. Parametric Equations 1. Parametric Equations 2. Parametric Equations 3. Parametric Equations 4. Introduction to Function Inverses. Function Inverse Example 1. Function Inverses Example 2. Function Inverses Example 3. Basic Complex Analysis. Exponential form to find complex roots. Complex Conjugates. Series Sum Example. Complex Determinant Example. 2003 AIME II Problem 8. Logarithmic Scale. Vi and Sal Explore How We Think About Scale. Vi and Sal Talk About the Mysteries of Benford's Law. Benford's Law Explanation (Sequel to Mysteries of Benford's Law).

Students often encounter grave difficulty in calculus if their algebraic knowledge is insufficient. This course is designed to provide students with algebraic knowledge needed for success in a typical calculus course. We explore a suite of functions used in calculus, including polynomials (with special emphasis on linear and quadratic functions), rational functions, exponential functions, and logarithmic functions. Along the way, basic strategies for solving equations and inequalities are reinforced, as are strategies for interpreting and manipulating a variety of algebraic expressions. Students enrolling in the course are expected to have good number sense and to have taken an intermediate algebra course.

This six week course will help students prepare for the AP* Calculus AB Exam. * AP Calculus is a registered trademark of the College Board, which was not involved in the production of, and does not endorse, this product.

This course is designed for high school students preparing to take the AP* Statistics Exam. * AP Statistics is a registered trademark of the College Board, which was not involved in the production of, and does not endorse, this product.

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.

This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.

18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity.

This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality; law of large numbers; and central limit theorem.

This course, which is geared toward Freshmen, is an undergraduate seminar on mathematical problem solving. It is intended for students who enjoy solving challenging mathematical problems and who are interested in learning various techniques and background information useful for problem solving. Students in this course are expected to compete in a nationwide mathematics contest for undergraduates.

This course provides an introduction to the theory and practice of quantum computation. Topics covered include: physics of information processing, quantum logic, quantum algorithms including Shor's factoring algorithm and Grover's search algorithm, quantum error correction, quantum communication, and cryptography.

This course is an introduction to the basics of random matrix theory, motivated by engineering and scientific applications.

This graduate-level subject explores various mathematical aspects of (discrete) random walks and (continuum) diffusion. Applications include polymers, disordered media, turbulence, diffusion-limited aggregation, granular flow, and derivative securities.

This course covers the fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and the interchange of limit operations. It shows the utility of abstract concepts and teaches an understanding and construction of proofs. MIT students may choose to take one of three versions of Real Analysis; this version offers three additional units of credit for instruction and practice in written and oral presentation.

The three options for 18.100:

• Option A (18.100A) chooses less abstract definitions and proofs, and gives applications where possible.
• Option B (18.100B) is more demanding and for students with more mathematical maturity; it places more emphasis from the beginning on point-set topology and n-space, whereas Option A is concerned primarily with analysis on the real line, saving for the last weeks work in 2-space (the plane) and its point-set topology.
• Option C (18.100C) is a 15-unit variant of Option B, with further instruction and practice in written and oral communication. This fulfills the MIT CI requirement.

Learn how to use regression models, the most important statistical analysis tool in the data scientist's toolkit. This is the seventh course in the Johns Hopkins Data Science Specialization.

In this undergraduate level seminar series, topics vary from year to year. Students present and discuss the subject matter, and are provided with instruction and practice in written and oral communication. Some experience with proofs required. The topic for fall 2008: Computational algebra and algebraic geometry.

18.104 is an undergraduate level seminar for mathematics majors. Students present and discuss subject matter taken from current journals or books. Instruction and practice in written and oral communication is provided. The topics vary from year to year. The topic for this term is Applications to Number Theory.