How You Can Make Almost Anything

14.381 Statistical Method in Economics (Updated Course) This course is divided into two sections, Part I and Part II. Part I, found here, provides an introduction to statistical theory. Topics include normal distribution, limit theorems, Bayesian concepts, and testing, among others. Part II can be found by visiting 14.381 Fall 2006.

21W.794 Graduate Technical Writing Workshop (New Course) This course is designed to improve the student's ability to communicate technical information. It covers the basics of working with sources, including summarizing and paraphrasing, synthesizing source materials, citing, quoting, and avoiding plagiarism. It also covers how to write an abstract and a literature review. In addition, we will cover communication concepts, tools, and strategies that can help you understand how engineering texts work, and how you can make your texts work more effectively.This course is limited to MIT graduate engineering students based on results of the Graduate Writing Exam.

6.057 Introduction to MATLAB (Updated Course) This is an accelerated introduction to MATLAB® and its popular toolboxes. Lectures are interactive, with students conducting sample MATLAB problems in real time. The course includes problem-based MATLAB assignments. Students must provide their own laptop and software. This is great preparation for classes that use MATLAB.

"I'm determined to teach myself the calculus, linear algebra, statistics and other math used in quantitative finance (and maybe even relativity and quantum mechanics, if I get ambitious).
In my day job I work for an investment firm and I use various multi-factor equity risk models and other risk analytics tools, and I decided a year or so ago to rekindle a youthful aptitude for math and really make an effort to understand what goes on "under the hood" of these models and analytics.
I'm smart enough to realize I can learn more if I let MIT professors teach me, rather than try to teach myself all by myself.
It's been an incredible experience, watching the classroom videos and reading from the books.
Keep up the great work!"
-Mark, OCW Supporter

18.335J Introduction to Numerical Methods (Updated Course) This course offers an advanced introduction to numerical analysis, with a focus on accuracy and efficiency of numerical algorithms. Topics include sparse-matrix/iterative and dense-matrix algorithms in numerical linear algebra (for linear systems and eigenproblems), floating-point arithmetic, backwards error analysis, conditioning, and stability. Other computational topics (e.g., numerical integration or nonlinear optimization) are also surveyed.

STS.081 Innovation Systems for Science, Technology, Energy, Manufacturing, and Health (New Course) This course focuses on science and technology policy—it will examine the science and technology innovation system, including case studies on energy, computing, advanced manufacturing, and health sectors, with an emphasis on public policy and the federal government's role in that system.