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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

# Numeric types
While SymPy primarily focuses on symbols, it is impossible to have a completely symbolic system without the ability to numerically evaluate expressions. Many operations will directly use numerical evaluation, such as plotting a function or solving an equation numerically. 

SymPy has 3 numeric types: rational, real, and integers. Since rational is the new one, let’s discuss it here:
## Rational
The rational class represents a rational number as a pair of two integers: the numerator and the denominator.

``` python3 
Rational(1, 4) 
```
represents $\frac{1}{4}$

``` python3 
Rational(5, 3) 
```
represents $\frac{5}{3}$

All the arithmetic operations can be performed on these rational numbers. Let's see an implementation of this below:

This lesson discusses numeric types and evaluation in SymPy.

Introduction

Python Refresher

Arrays

Plotting

Systems of Linear Equations

Symbolic Computation

Scientific Algorithms

Random Variables

Applications

Conclusion

Appendix

Python for Scientists and Engineers Exam

Numerical Evaluation

Numeric types

Rational