HomeCoursesPython for Scientists and Engineers

4.8

Intermediate

13h

Python for Scientists and Engineers

Gain insights into Python for scientific computing. Explore arrays, plotting, linear equations, and algorithms using NumPy, Matplotlib, SciPy. Delve into applying tools with practical exercises.

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Overview

Content

Reviews

If you're a scientist or an engineer interested in learning scientific computing, this is the place to start. In this course, you'll learn to write your own useful code to perform impactful scientific computations. Along the way, your understanding will be tested with periodic quizzes and exercises. Topics covered in this course include arrays, plotting, linear equations, symbolic computation, scientific algorithms, and random variables. You’ll also be exposed to popular Python packages like NumPy, Matplotlib, SciPy, and others. In the last part of the course, the application section will test your ability to recall and apply the tools you have studied into newly learned scientific concepts. At the end of this course, you'll be equipped with the tools necessary for everyday scientific computation.

If you're a scientist or an engineer interested in learning scientific computing, this is the place to start. In this course, y...Show More

TAKEAWAY SKILLS

Python Basics

Arrays

Plotting

Systems of Linear Equations

Symbolic Computation

Scientific Algorithms

Random Variables

Content

98 Lessons11 Quizzes1 Assessment1 Challenge

Introduction

2 Lessons

Get familiar with Python's advantages in scientific computing and essential programming libraries.

Introduction

About This Course

Python Refresher

12 Lessons

Get started with Python essentials, including variables, operators, loops, functions, and packages.

Data Types and Variables

Operators

Conditional Statements

Tuples and Dictionaries

Using Python Packages

Quiz 1!

Exercise: Check Sum

Solution Review: Check Sum

Arrays

13 Lessons

Examine NumPy arrays, multidimensional arrays, array operations, indexing, data processing, and smart programming techniques.

Plotting

11 Lessons

Apply your skills to create and customize 2-D and 3-D plots using matplotlib.

Systems of Linear Equations

7 Lessons

Solve problems in systems of linear equations, eigenvalues, matrix operations, and sparse matrices.

Symbolic Computation

17 Lessons

Follow the process of using SymPy for symbolic computation, including algebra, calculus, and equation solving.

Scientific Algorithms

13 Lessons

Master scientific algorithms using SciPy for integration, interpolation, optimization, and Fourier transforms.

Random Variables

9 Lessons

Learn how to use random variables, distributions, histograms, percentiles, and prediction simulations.

Applications

10 Lessons

Get started with hands-on applications of Python in optical systems, transfer functions, and harmonographs.

10.

Conclusion

2 Lessons

Go hands-on with future learning in data science and machine learning skills.

11.

Appendix

2 Lessons

Grasp the fundamentals of efficient file I/O with NumPy and LaTeX formatting in matplotlib.

Python for Scientists and Engineers Exam

Assessment

Certificate of Completion

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Show License and Attributions

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Code Feedback

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AI Code Mentor

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