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Browse materialsMIT 2.993J · Spring 2005

Introduction to Numerical Analysis for Engineering (13.002J)

Subjects: Engineering · Mathematics · Mechanical Engineering

Art: Robison, John, 1739-1805., Steam engine - Mr. Watt's double steam engine from his specification…, 1822 · Public domain

Instructor: Prof. Henrik Schmidt
Term: Spring 2005
Level: Undergraduate
What's inside: 1 lecture note · 1 reading · 57 other files · 4 web pages
Materials open: MIT OCW

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About this course

Source: MIT OpenCourseWare 2.993J Introduction to Numerical Analysis for Engineering (13.002J), Spring 2005, Prof. Henrik Schmidt — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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Prerequisites are not listed here. Check MIT's own syllabus for this course.

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A lecture sequence of 12 items is confirmed. Assignment and exam materials exist too, but MIT's own order for them could not be verified, so they're shown as materials below rather than a sequence.

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Syllabus

Class Survey-Spring 2005PDF Download

Lecture Notes

45 files

Assignments

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Exams

Take-home ExamPDF Download

MIT OpenCourseWare, Prof. Henrik Schmidt, 2.993J Introduction to Numerical Analysis for Engineering (13.002J), Spring 2005.

License: CC BY-NC-SA 4.0 · Edition: Spring 2005 · Open the original course on OCW ↗

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Introduction to Numerical Analysis for Engineering (13.002J)

Before you start

What's here, and what isn't

Not included here

Materials by section

Syllabus

Lecture Notes

Assignments

Exams

Lecture 1: Introduction Computer Architecture Number Representations Recursion

Lecture 2: Error Propagation Error Estimation Condition Numbers

Lecture 3: Linear Systems of Equations: Cramer’s Rule Gaussian Elimination

Lecture 4: Linear Systems: Gaussian Elimination Pivoting LU Factorization Error Analysis

Lecture 5: Linear Systems: Tri-diagonal Systems Special Matrices

Lecture 6: Linear Systems: Iterative Methods Convergence of Iterative Schemes

Lecture 7: Roots of Non-linear Equations: Bisection Newton-Ralphson Iteration

Lecture 8: Interpolation of Functions by Polynomials Lagrange Interpolation Triangular Family

Lecture 9: Numerical Differentiation and Integration Error Estimates

Lecture 10: Ordinary Differential Equations Initial Value Problems: Euler and Runge-Kutta Methods

Lecture 11: Ordinary Differential Equations (cont.) Boundary Value Problems: Finite Difference Methods

Lecture 12: Minimization Problems Least Square Approximation Optimization