Online courses directory (19947)

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Learn to produce Deep House music from grammy nominated producer Davidson Ospina

formadores

Stories, Rare Photographs and Videos From The Ancient Ruins And World Heritage Sites Of India. An Experiential Journey.

This course introduces students to the legal, economic, and structural issues that both shape our energy practices and p

The Ultimate Confidence Booster For Microsoft Project 2010 And Your Ticket to A+ Project Manager Status.

The apps market is growing TWICE AS FAST as the internet boom in the 90s. Join out iPhone app development tutorial.

A thorough guide to using Antares Autotune 7. This sequence of video Autotune 7 tutorials answers all questions.

enabling doctors to be more effective and efficient

Reparaci

Learn simple steps to guide you in asking the right questions and achieving amazing results in the New Year.

Video tutorials + Practical exercise. Learn the basics of design 2D & 3D now!

Momentum Maker - Techniques and tools for breaking into the continual flow of action required for long term success.

Learn how to market yourself until you are the biggest brand in your field.

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.

Together, this course and 8.06 Quantum Physics III cover quantum physics with applications drawn from modern physics. Topics covered in this course include the general formalism of quantum mechanics, harmonic oscillator, quantum mechanics in three-dimensions, angular momentum, spin, and addition of angular momentum.

In this course on the mathematics of infinite random matrices, students will learn about the tools such as the Stieltjes transform and Free Probability used to characterize infinite random matrices.

This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language.

The course is designed to help prepare students for 6.01 Introduction to EECS I. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

This is a course on the fundamentals of probability geared towards first- or second-year graduate students who are interested in a rigorous development of the subject. The course covers most of the topics in 6.431 (sample space, random variables, expectations, transforms, Bernoulli and Poisson processes, finite Markov chains, limit theorems) but at a faster pace and in more depth. There are also a number of additional topics, such as language, terminology, and key results from measure theory; interchange of limits and expectations; multivariate Gaussian distributions; deeper understanding of conditional distributions and expectations.

This course runs parallel to 8.02, but assumes that students have some knowledge of vector calculus. The class introduces Maxwell's equations, in both differential and integral form, along with electrostatic and magnetic vector potential, and the properties of dielectrics and magnetic materials.

This class was taught by an undergraduate in the Experimental Study Group (ESG). Student instructors are paired with ESG faculty members, who advise and oversee the students' teaching efforts.