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Python for Scientists and Engineers

Name: Python for Scientists and Engineers
Price: 59 USD
Author: Khayyam Hashmi

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.

5.0

98 lessons

13h

Created by Khayyam Hashmi

What's included

98 lessons across 11 modules
11 quizzes with instant feedback
AI Tutor on every lesson

Join 3.1 million developers at

What You'll Learn

Write Python programs using data types, operators, conditionals, loops, functions, and lambdas
Manipulate NumPy vectors and multidimensional arrays using indexing, slicing, reshaping, and vectorization
Process array data by computing statistics (mean, std, variance, min, max) and filtering with conditions
Create and save publication-style 2-D and 3-D Matplotlib plots with subplots, legends, and axis controls
Solve linear systems and matrix problems using NumPy/SciPy (solve, eigenvalues, sparse matrices, norms)
Perform symbolic algebra and calculus in SymPy (simplify, solve, derivatives, integrals, limits, series, ODEs)
Apply SciPy algorithms for integration, interpolation, curve fitting, optimization, and Fourier transforms

Learning Roadmap

98 Lessons11 Quizzes1 Assessment1 Challenge

Introduction

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

Introduction

About This Course

Python Refresher

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

Showcase your accomplishment by sharing your certificate of completion.

Show License and Attributions

About this course

WHY I WROTE THIS COURSE

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.

ABOUT THE AUTHOR

Khayyam Hashmi

Computer scientist and Generative AI and Machine Learning specialist. VP of Technical Content @ educative.io.

Learn more about Khayyam

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