1
00:00:00,000 --> 00:00:05,000
Python fundamentals with Artificial Intelligence
2
00:00:05,000 --> 00:00:08,000
Python control statements and practice
3
00:00:08,000 --> 00:00:14,000
This is a session to understand and practice Python’s basic control statements: if, for, and while.
4
00:00:14,000 --> 00:00:18,000
You will learn essential elements for implementing complex algorithms.
5
00:00:18,000 --> 00:00:23,000
Today, in the fifth Python lecture, we’ll cover control statements, collections, and collection methods,
6
00:00:23,000 --> 00:00:27,000
working through various topics with hands-on practice.
7
00:00:27,000 --> 00:00:37,000
In control statements, we’ll learn conditionals and loops, and in collections, we’ll take a closer look at lists, tuples, sets, and dictionaries.
8
00:00:37,000 --> 00:00:41,000
We’ll also learn how to use collection methods.
9
00:00:41,000 --> 00:00:43,000
Let’s review control statements.
10
00:00:43,000 --> 00:00:49,000
Control statements are the core structures that control the flow of execution in a program.
11
00:00:49,000 --> 00:00:52,000
They consist of conditionals and loops.
12
00:00:52,000 --> 00:00:55,000
First, the if statement among conditionals.
13
00:00:55,000 --> 00:01:00,000
It performs branching to execute different code depending on the condition.
14
00:01:00,000 --> 00:01:02,000
while and for loops
15
00:01:02,000 --> 00:01:10,000
They repeatedly execute code while a certain condition is satisfied, or repeat according to a sequence or range.
16
00:01:10,000 --> 00:01:16,000
The range function is a useful function that creates a sequence of integers as needed.
17
00:01:16,000 --> 00:01:19,000
Next are other control statements.
18
00:01:19,000 --> 00:01:22,000
Now it’s time to learn about the remaining control statements.
19
00:01:22,000 --> 00:01:26,000
These include the break statement, continue statement, and pass statement.
20
00:01:26,000 --> 00:01:31,000
These commands help you control code more flexibly.
21
00:01:31,000 --> 00:01:35,000
The break statement forcibly terminates a loop,
22
00:01:35,000 --> 00:01:40,000
and the continue statement skips the current iteration and moves on to the next one.
23
00:01:40,000 --> 00:01:46,000
And the pass statement executes nothing—in other words, it simply passes.
24
00:01:46,000 --> 00:01:50,000
The next topic is collections.
25
00:01:50,000 --> 00:01:55,000
We’re going to deal with lists, tuples, sets, and dictionaries.
26
00:01:55,000 --> 00:02:02,000
A list is a sequence data type that allows duplicate values and supports adding, modifying, and deleting elements.
27
00:02:02,000 --> 00:02:08,000
A tuple is similar to a list, but it is read-only.
28
00:02:08,000 --> 00:02:13,000
A set does not allow duplicate values, and you can add and remove elements.
29
00:02:13,000 --> 00:02:19,000
Lastly, a dictionary is a non-sequence data type made up of key–value pairs.
30
00:02:19,000 --> 00:02:26,000
We’ll look at each collection in more detail and see how it can be used.
31
00:02:26,000 --> 00:02:31,000
Lastly, it’s time to learn about collection methods.
32
00:02:31,000 --> 00:02:36,000
It’s important to understand the difference between functions and methods.
33
00:02:36,000 --> 00:02:41,000
Functions are used on their own, and methods are used together with an object.
34
00:02:42,000 --> 00:02:47,000
There are various methods that can be applied to lists, tuples, and sets.
35
00:02:47,000 --> 00:02:53,000
Using these methods, you can manage collections more efficiently.
36
00:02:53,000 --> 00:02:56,000
Assignment guide and wrap-up
37
00:02:56,000 --> 00:03:01,000
Based on what you learned today, try a few assignments.
38
00:03:01,000 --> 00:03:07,000
These assignments will help you practice and internalize the concepts we covered today.
39
00:03:07,000 --> 00:03:12,000
Practicing calculating an average, using lists and sets, and calculating Python scores, etc.,
40
00:03:12,000 --> 00:03:17,000
work through various problems to deepen your understanding.
41
00:03:17,000 --> 00:03:25,000
For student score calculation, write a program that takes multiple students’ scores as input and calculates and prints the total and average.
42
00:03:25,000 --> 00:03:29,000
Python’s control statements offer a variety of features.
43
00:03:29,000 --> 00:03:38,000
The break statement forcibly terminates a loop, and the continue statement skips the current iteration and moves on to the next one.
44
00:03:38,000 --> 00:03:44,000
Also, the pass statement is a command that does nothing, allowing you to add code later.
45
00:03:44,000 --> 00:03:49,000
In this example, we use a nested for-loop to print the multiplication table.
46
00:03:49,000 --> 00:03:56,000
The outer loop repeats from the 1-times table to the 9-times table, and the inner loop prints the products in each table.
47
00:03:57,000 --> 00:04:10,000
To print each table’s multiplication results neatly, we used print("-------------") to insert a separator line between the tables.
48
00:04:10,000 --> 00:04:15,000
We also practiced adding and removing elements in a set.
49
00:04:15,000 --> 00:04:21,000
Finally, we learned how to work with key–value pairs in dictionaries.
50
00:04:21,000 --> 00:04:28,000
We calculate and print the average of the tuple (43, 55, 63, 20, 91).
51
00:04:28,000 --> 00:04:34,000
Using the list [1, 2, 2, 3, 4, 4], we perform various operations.
52
00:04:34,000 --> 00:04:40,000
We take the Python scores of five students as input, then calculate and print the total and average.
53
00:04:40,000 --> 00:04:44,000
That’s it for today’s class.
54
00:04:44,000 --> 00:04:49,000
If you have any questions about the lesson, feel free to ask anytime.
55
00:04:49,000 --> 00:04:51,000
Thank you.
Python Basics with Artificial Intelligence
Lecture Overview and Learning Objectives
Understand how basic Python control statements (if, for, while) work and how to use them
Practice conditional and loop structures for implementing complex algorithms
Learn the characteristics and usage of collection data types (list, tuple, set, dictionary)
Practice managing data efficiently using collection methods
Control Statements: Conditionals and Loops
Control statements: Structures that branch or repeat the program’s execution flow depending on conditions
if statement: Branch processing that executes different code depending on a condition
while statement: Repeatedly executes code while a given condition is true
for statement: Repeats a fixed number of times over a sequence (such as a list) or a range
range() function: Generates an integer sequence of the required length for use in loops
Other Control Statements: break, continue, pass
break: Immediately terminates the current loop
continue: Skips the current iteration and proceeds to the next
pass: Performs no action, used as a placeholder for code to be added later
Used to precisely control execution flow in complex loop structures
Characteristics of Collection Data Types
list: Allows duplicates, ordered, can be added to, modified, and deleted
tuple: Similar to a list, but read-only (cannot be modified)
set: Does not allow duplicates, order is not guaranteed, elements can be added and removed
dictionary: A non-sequence data type composed of key–value pairs
Understand the structure and features of each collection and choose the right one for each situation
Collection Methods and Their Use
Function: A block of code that is called and used independently
Method: A function that belongs to a specific object (e.g., list, tuple, set) and manipulates that object
Improve data management efficiency using various methods applicable to list, tuple, and set
Practice such as adding/removing set elements and accessing/modifying dictionary key–value pairs
Practice Examples and Assignments
Print the multiplication table using nested for loops (including separators between each set of tables)
Practice adding/removing set elements and handling dictionary key–value pairs
Write a program that calculates the average of given tuple scores
Practice processing data that includes duplicates using a list
Implement a program that takes multiple students’ scores as input and calculates total and average
Reinforce concepts by combining control statements and collections to solve real-world problems
