Data Science using Python

Data Science using Python


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SKU: cid_72338 Category:
About the course

Computing has always played an important role in science and engineering. Sometimes it is also called "third pillar" along with experiments and theory. In this course, you will learn computational science and engineering with the help of the Python programming language. This course covers the fundamental concepts of python variables, functions, and packages. Then it introduces control structures and basic numerical algorithms. In this course, you will also learn about interpolation, integration, differentiation, ODE and PDE solvers and basic linear algebra.
The course mainly focuses on the practical approach and expects you to try hands-on with the exercises to get completely proficient in working with.

Target Audience

The course can be taken by:

Students: All students who are pursuing professional graduate/post-graduate courses related to computer science / Information Technology.

Teachers/Faculties: All computer science teachers/faculties who wish to acquire new skills.

Professionals: All working professionals, who wish to enhance their skills.

Course Features
  • 24X7 Access: You can view lectures as per your own convenience.
  • Online lectures: ~30 hours of online lectures with high-quality videos.
  • Hands-on practice: Includes source code files for hands-on practice.
  • Updated Quality content: Content is the latest and gets updated regularly to meet the current industry demands.
Test & Evaluation

Each lecture will have a quiz containing a set of multiple-choice questions. Apart from that, there will be a final test based on multiple-choice questions.

Your evaluation will include the overall scores achieved in each lecture quiz and the final test.


Certification requires you to complete all the lectures, quizzes, and the final test.

Topics to be covered

Module 01: About computer, python: Variables and Array

  • Introduction to computers
  • Python variables
  • Numpy arrays and its functions

Module 02: Python: Control structures, Programming style

  • Basic python control structures
  • Python packages and programming style
  • Some suggestions on programming

Module 03: Plotting, Errors, Data input/output

  • Plotting functions in Python
  • Errors analysis & Nondimensionalization
  • Data I/O & Mayavi

Module 04: Interpolation

  • Lagrange Interpolation scheme
  • Interpolation two dimensions

Module 05: Numerical Integration

  • Integration using Newton-Cotes
  • Integration using Gaussian quadrature
  • Gaussian quadrature continued

Module 06: Differentiation, ODE solvers

  • Numerical differentiation of functions
  • Ordinary differential equations solver
  • ODE solver continued

Module 07: Forier transforms, PDE solvers

  • DiscreteFourier transform
  • PDE solver: Diffusion equation in spectral method
  • PDE solver: Diffusion equation using finite difference
  • PDE solver: Wave equation using finite difference

Module 08: Linear Algebra, Summary

  • Ax = b using the Gaussian elimination method
  • Conclusion