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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**

Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.

Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success

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 |

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