Both in lists and in arrays, elements are accessed using regular square brackets.
Let's remember the difference between indexing and slicing.
 - In order to get a single element, we just need to specify the index of this element in square brackets (start counting from 0).
 - Therefore, in order to obtain a sequence from the original array, we should use slices.

We start with a simple indexing. Let's look at the next image.

Get the first element from the following array:

import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the first element
print(arr[0])

Get the second element from the following array:

import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the second element
print(arr[1])

Get the third and the fourth elements from the following array and add them:

import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Adding the third and the fourth elements
print(arr[2] + arr[3])

Now it's time to look at using slicing. First, let's look at the syntax of slicing: `array[start: end: step]` respectively:
- start - the index from which to start slicing.
- end - the index till which the slicing ends (! this index is not included).
- step - this parameter determines the increments between the indices.

Let's look at the next image.

In this section we will get acquainted with what the NumPy library is, as well as learn how to create an array.

In this section we will get acquainted with arrays of different dimensions, and understand the difference between them.

In this section we should recall what slices are and learn how to make them for arrays of different dimensions. We shall also learn to refer to elements in an array using their indexes.

In this section we will learn how to reshape arrays and also how to concatenate an array. Moreover we will learn how to sort an array. Also we will learn about such an interesting method that is often used for arrays, namely: copy().