| Week |
Subject |
Related Preparation |
| 1) |
Review of single-variable calculus. |
|
| 2) |
Functions of several variables. Partial derivatives, differentials, implicit functions, Jacobian. |
|
| 3) |
Vector functions. Gradient, divergence, curl and Laplacian. Directional derivative. |
|
| 4) |
Maxima and minima, Lagrange multipliers. |
|
| 5) |
Multiple integrals. Line integrals, Green's theorem. |
|
| 6) |
Surface integrals, the divergence theorem, Stoke's theorem. |
|
| 7) |
Cylindrical and spherical coordinates. |
|
| 8) |
Applications of vector calculus. |
|
| 9) |
Functions of a complex variable. Continuity and differentiation. |
|
| 10) |
Complex integration. Cauchy's theorem and integral formula. |
|
| 11) |
Taylor and Laurent series. Poles and residues. |
|
| 12) |
Conformal mapping and applications. |
|
| 13) |
Fourier series. |
|
| 14) |
Fourier transform. |
|
| |
Program Outcomes |
Level of Contribution |
| 1) |
1. To be able to follow and critically analyze scientific literature and use it effectively in solving engineering problems. |
1 |
| 2) |
To be able to design, plan, implement and manage original projects related to Big Data Analytics and Management. |
1 |
| 3) |
To be able to carry out studies on Big Data Analytics and Management independently, take scientific responsibility and critically evaluate the results obtained. |
1 |
| 4) |
Effectively present the results of his/her research and projects in written, oral and visual form in accordance with academic standards. |
1 |
| 5) |
To be able to conduct independent research in the field of Big Data Analytics and Management, develop original ideas and transfer this knowledge to practice. |
1 |
| 6) |
Uses advanced theoretical and practical knowledge specific to the field of Big Data Analytics and Management effectively. |
1 |
| 7) |
Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering applications. |
1 |