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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Python3

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.

Python for Scientists and Engineers


Differentiation is the process of finding a function that outputs the rate of change of one variable with respect to another.

SymPy provides the functionality of symbolically calculating the derivatives of a function. 
 
## First-order derivatives
Derivatives are computed with the `diff` function, which recursively uses the various differentiation rules. 

<center>


$y=x^{4}+x^{3}+x^{2}$

$$\frac{dy}{dx} =4x^3 +3x^2+2x$$

</center>

We will be exploring different types of derivatives using SymPy. The SymPy `diff()` function takes a minimum of two arguments: the function to be differentiated and the variable with respect to which the differentiation is performed.

``` python3
diff(y, x)
```
Let's look at an implementation of this:


Differentiation is the process of finding a function that outputs the rate of change of one variable with respect to another.

SymPy provides the functionality of symbolically calculating the derivatives of a function. 
 
# First-order derivatives
Derivatives are computed with the `diff` function, which recursively uses the various differentiation rules. 

<center>


$y=x^{4}+x^{3}+x^{2}$

$$\frac{dy}{dx} =4x^3 +3x^2+2x$$

</center>

We will be exploring different types of derivatives using SymPy. The SymPy `diff()` function takes a minimum of two arguments: the function to be differentiated and the variable with respect to which the differentiation is performed.

``` python3
diff(y, x)
```
Let's look at an implementation of this:

This lesson discusses first and higher order derivatives. 

Introduction

Python Refresher

Arrays

Plotting

Systems of Linear Equations

Symbolic Computation

Scientific Algorithms

Random Variables

Applications

Conclusion

Appendix

Python for Scientists and Engineers Exam

Differentiation

First-order derivatives