Python for Engineers and Scientists / basic to advanced

The goal of “Python for Engineers and Scientists” is to provide programming, mathematical, and graphical tools for professionals across various fields.

Why should you take this course?

Both Python and the scientific ecosystem libraries taught here are FREE and open-source tools. This makes it easier to adopt these tools in both workplace and academic settings.

Moreover, the language and its libraries have been growing worldwide with a super active community. I’ve observed this since 2015 when I did R&D internships at a nuclear energy company.

Don’t fall behind, my friend!

What do you gain by enrolling in this course?

This is the most comprehensive course with the best cost/benefit ratio on Python and its scientific ecosystem. In addition to around 15 hours of content, students have access to the Q&A forum, where we already have constructive interactions with all students and many questions and answers already addressed. You’ll also have access to all the materials/codes created during the class, all structured and organized!

What will I learn?

In general, the course content includes:

– Python Fundamentals: You’ll learn everything from installation to more advanced topics like object-oriented programming. Also, you’ll cover useful day-to-day topics like task automation.

– Sympy: You’ll master symbolic algebra manipulation, solving systems of equations, differential equations, and calculus functions. Additionally, there are plenty of exercises and challenges (proposed and solved). Sympy is a great substitute for Matlab.

– Numpy: You’ll dive deep into the powerful array structure of Numpy.

– Pandas: You’ll learn the best Excel replacement we have today. We’ll work on filters, pivot tables, graphs, and real data handling with Pandas.

– Matplotlib: You’ll gain an in-depth understanding of Matplotlib’s objects for creating charts and dashboards.

– Scipy: You’ll explore the “big boy” of computational mathematics in Python. We’ll cover linear algebra, integrals, and numerical solutions to ODEs, with exercises (proposed and solved).

I invite all of you to watch the introductory lesson where I showcase the learning structure of the course.