Learn Python Programming: An Intermediate Journey

Master Python Through Hands-On Exercises for Real-World Applications + 77 Coding Exercises

What you'll learn

Understand and set up Python coding environment using Google Colab.

Learn to create, access, and modify lists in Python effectively.

Perform list operations like concatenation, repetition, and membership testing.

Explore common list methods such as append, remove, sort, and clear.

Work with tuples and differentiate them from lists.

Learn tuple operations, slicing, and packing/unpacking techniques.

Use tuple methods like count() and index() for basic operations.

Understand Python sets and their differences from lists and tuples.

Perform set operations like union, intersection, and difference.

Explore advanced set techniques like comprehension and frozensets.

Apply sets to solve practical problems like finding common elements or unique values.

Understand dictionaries and their comparison with other data structures.

Learn to add, remove, and update key-value pairs in dictionaries.

Perform operations like merging dictionaries and using nested dictionaries.

Use formatted printing techniques like f-strings and format() for better output presentation.

Practice alignment, padding, and number formatting in Python.

Requirements

Understanding Numeric Data Types: Familiarity with integers, floats, and basic arithmetic operations in Python.

Boolean Data Types: Knowledge of True/False values and logical operators like and, or, and not.

Working with Strings: Ability to manipulate strings using slicing, concatenation, and common string methods.

Conditional Statements: Proficiency in using if, elif, and else to control program flow.

Loop Control Flow: Experience with loops like for and while, including using break and continue.

Defining and Using Functions: Understanding how to write and call functions, pass arguments, and return values.

Description

Are you ready to elevate your Python programming skills and unlock the full potential of its powerful data structures? This intermediate-level course is designed to bridge the gap between basic Python knowledge and advanced programming techniques. Whether you’re aiming to enhance your career, work on real-world projects, or simply deepen your Python expertise, this course is the perfect next step.What will you learn?Master Python Lists: Learn to create, modify, and manipulate lists for effective data handling.Explore Tuples and Sets: Understand their unique properties and discover practical applications, such as ensuring data integrity and performing efficient operations.Work with Dictionaries: Dive deep into managing key-value pairs and leveraging them for complex data organization.Perform Advanced Operations: Use slicing, looping, and membership testing across all data structures.Format Your Output: Learn advanced printing techniques using f-strings and format functions to make your code professional and clean.What makes this course special?Interactive Hands-On Practice: Each lecture is paired with coding exercises designed to apply concepts to real-world problems, such as finding unique values in lists or merging dictionaries.Problem-Solving Approach: You’ll learn not just the "how" but also the "why," equipping you to think critically and solve challenges independently.Beginner-Friendly Content: Each concept is explained in clear and concise terms, ensuring that you can follow along with ease.Coding Exercises: We dive into solving 77 coding exercises in order for you to understand the Python concepts in practice.By the end of this course, you will have the confidence to work with Python’s most essential data structures and apply your skills to build efficient, scalable applications. This course is perfect for anyone who has a basic understanding of Python and wants to take their coding journey to the next level.Start your Python mastery today and transform your programming potential!

Overview

Section 1: Coding environment

Lecture 1 Python using Google Colab

Section 2: Lists

Lecture 2 Introduction to lists: Creating and accessing lists

Lecture 3 Coding exercise #1: Modifying a list

Lecture 4 Coding exercise #2: Modifying a list using append(), extend(), insert()

Lecture 5 Coding exercise #3: Modifying a list using remove(), del, clear()

Lecture 6 Coding exercise #4: List operations (Part 1 concatenation `+')

Lecture 7 Coding exercise #5: List operations (Part 2 repetition `*')

Lecture 8 Coding exercise #6: List operations (Part 3 membership test `in', `not in')

Lecture 9 Coding exercise #7: List operations (Part 4 iteration using for loops)

Lecture 10 Coding exercise #8: Common list methods (Part 1: `len()')

Lecture 11 Coding exercise #9: Common list methods (Part 2: `index()')

Lecture 12 Coding exercise #10: Common list methods (Part 3: `count()')

Lecture 13 Coding exercise #11: Common list methods (Part 4: `sort()')

Lecture 14 Coding exercise #12: Common list methods (Part 5: `reverse()')

Lecture 15 Coding exercise #13: Common list methods (Part 6: `copy()')

Lecture 16 Coding exercise #14: Appending two lists

Lecture 17 Coding exercise #15: Shopping list

Lecture 18 Coding exercise #16: Sum of numbers

Lecture 19 Coding exercise #17: To reverse a list

Lecture 20 Coding exercise #18: Largest number in a list

Section 3: Tuples

Lecture 21 Introduction to tuples and their difference with lists

Lecture 22 Coding exercise #19: Creating different types of tuples

Lecture 23 Coding exercise #20: Accessing elements and slicing

Lecture 24 Coding exercise #21: Concatenation and Repetition

Lecture 25 Coding exercise #22: Packing and unpacking

Lecture 26 Coding exercise #23: Unpacking a tuple

Lecture 27 Coding exercise #24: Using count() and index() functions

Lecture 28 Coding exercise #25: Membership testing

Lecture 29 Coding exercise #26: Iterating through a tuple

Lecture 30 Coding exercise #27: Element-wise sum of two tuples

Lecture 31 Coding exercise #28: To print first and last elements

Lecture 32 Coding exercise #29: To calculate the number os elements of a tuple

Lecture 33 Coding exercise #30: Number of cities

Lecture 34 Coding exercise #31: Check the user input

Section 4: Sets

Lecture 35 Introduction to sets and its comparison with tuples and lists

Lecture 36 Coding exercise #32: Creation of sets

Lecture 37 Coding exercise #33: Using add(), remove() and discard() functions for a set

Lecture 38 Coding exercise #34: Combining two sets using pipe operator and union() function

Lecture 39 Coding exercise #35: Set intersection using two methods

Lecture 40 Coding exercise #36: Set difference using two methods

Lecture 41 Coding exercise #37: Symmetric difference

Lecture 42 Coding exercise #38: Membership testing

Lecture 43 Coding exercise #39: Iterating through a set

Lecture 44 Coding exercise #40: Subset and superset

Lecture 45 Coding exercise #41: Set comprehension using for loops

Lecture 46 Coding exercise #42: Set comprehension for even numbers

Lecture 47 Coding exericse #43: Set comprehension for vowel letters

Lecture 48 Coding exercise #44: Set comprehension for vowel letters Part 2

Lecture 49 Coding exercise #45: Frozen sets

Lecture 50 Coding exercise #46: Chaining set method

Lecture 51 Coding exercise #47: To find unique words

Lecture 52 Coding exercise #48: To find common elements

Lecture 53 Coding exericse #49: Lottery draw

Lecture 54 Coding exercise #50: To check subset and superset

Lecture 55 Coding exercise #51: To check if a value is present in a set

Lecture 56 Coding exercise #52: To find the maximum and minimum numbers in a set

Lecture 57 Coding exercise #53: To find the third largest number

Lecture 58 Coding exercise #54: To find the pair with maximum product

Lecture 59 Coding exercise #55: Finding common elements of lists using sets

Lecture 60 Coding exercise #56: Finding unique values in a list using sets

Lecture 61 Coding exercise #57: Finding the 2nd smallest number in a list using sets

Section 5: Dictionaries

Lecture 62 Introduction to dictionaries

Lecture 63 Comparing dictionaries with lists, tuples, and sets

Lecture 64 Coding exercise #58: To add key-value pairs

Lecture 65 Coding exercise #59: To remove items from a dictionary

Lecture 66 Coding exercise #60: To iterate through a dictionary

Lecture 67 Coding exercise #61: To iterate through a dictionary 2

Lecture 68 Coding exercise #62: Having a new item in our dictionary

Lecture 69 Coding exercise #63: An example of a dictionary called `car'

Lecture 70 Coding exercise #64: Dictionaries and if conditions

Lecture 71 Coding exercise #65: To find the number of items in a dictionary

Lecture 72 Coding exercise #66: To merge or update two dictionaries

Lecture 73 Coding exercise #67: To loop through keys, values, and items()

Lecture 74 Coding exercise #68: To use nested dictionaries

Lecture 75 Coding exercise #69: Sum of all values in a dictionary

Lecture 76 Coding exercise #70: Multiply of all values in a dictionary

Section 6: Formatted printing

Lecture 77 Coding exercise #71: Formatted printing using f-strings

Lecture 78 Coding exercise #72: Formatted printing using format() function

Lecture 79 Coding exercise #73: Positional arguments

Lecture 80 Coding exercise #74: Named arguments

Lecture 81 Coding exercise #75: Alignment and padding

Lecture 82 Coding exercise #76: Formatting numbers

Lecture 83 Coding exercise #77: Adding commas to large numbers

Beginners in Python programming who want to strengthen their foundational skills.,Individuals familiar with basic Python concepts like data types and loops, seeking to enhance their knowledge.,Students looking to master essential data structures like lists, tuples, sets, and dictionaries.,Aspiring programmers aiming to understand how to handle and manipulate data effectively in Python.,Developers preparing to work on real-world Python projects with a focus on practical coding exercises.