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Computational science known as scientific computing is a multidisciplinary field that uses computing abilities. This field includes lessons on linear algebra such as applications to networks, structures, and estimation which are all important in the Engineering profession.

You are provided in this [course_title] with lessons that can help you understand programming high performance for engineering purposes. You will also encounter important calculus topics such as Fourier series in this course.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

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Course Credit: MIT

Course Curriculum

Course Introduction 00:04:00
Lecture 1: Four Special Matrices 00:54:00
Recitation 1: Key Ideas of Linear Algebra 00:49:00
Lecture 2: Differential Eqns and Difference Eqns 00:52:00
Lecture 3: Solving a Linear System 00:54:00
Lecture 4: Delta Function Day 00:55:00
Recitation 2 00:51:00
Lecture 5: Eigenvalues (Part 1) 00:56:00
Lecture 6: Eigen Values (part 2) and Positive Definite (part 1) 00:56:00
Lecture 7: Positive Definite Day 00:52:00
Lecture 8: Springs and Masses 00:55:00
Recitation 3 01:00:00
Lecture 9: Oscillation 00:57:00
Recitation 4 00:56:00
Lecture 10: Finite Differences in Time 00:54:00
Lecture 11: Least Squares (part 2) 00:53:00
Lecture 12: Graphs and Networks 00:50:00
Recitation 5 00:54:00
Lecture 14: Exam Review 00:52:00
Lecture 13: Kirchhoff’s Current Law 00:54:00
Recitation 6 00:54:00
Lecture 15: Trusses and A^(T)CA 00:46:00
Lecture 16: Trusses (part 2) 00:48:00
Lecture 17: Finite Elements in 1D (part 1) 00:54:00
Recitation 7 00:53:00
Lecture 18: Finite Elements in 1D (part 2) 00:51:00
Lecture 19: Quadratic/Cubic Elements 00:52:00
Lecture 20: Element Matrices; 4th Order Bending Equations 00:50:00
Recitation 8 00:48:00
Lecture 21: Boundary Conditions, Splines, Gradient, Divergence 00:53:00
Recitation 9 00:51:00
Lecture 22: Gradient and Divergence 00:51:00
Lecture 23: Laplace’s Equation 00:49:00
Lecture 24: Laplace’s Equation (part 2) 00:54:00
Lecture 25: Fast Poisson Solver (part 1) 00:52:00
Lecture 26: Fast Poisson Solver (part 2); Finite Elements in 2D 00:51:00
Lecture 27: Finite Elements in 2D (part 2) 00:52:00
Recitation 10 00:45:00
Lecture 28: Fourier Series (part 1) 00:49:00
Lecture 29: Fourier Series (part 2) 00:48:00
Recitation 11 00:54:00
Lecture 30: Discrete Fourier Series 00:50:00
Lecture 31: Fast Fourier Transform, Convolution 00:51:00
Recitation 12 00:51:00
Lecture 32: Convolution (part 2), Filtering 00:52:00
Lecture 33: Filters, Fourier Integral Transform 00:51:00
Lecture 34: Fourier Integral Transform (part 2) 00:51:00
Recitation 13 00:50:00
Lecture 35: Convolution Equations: Deconvolution 00:51:00
Lecture 36: Sampling Theorem 00:40:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

Course Reviews

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