Learn Core Python Basics taught by Googler

In this comprehensive Python course, you’ll be guided from complete beginner to confidently writing clean, efficient code for real-world applications.

You’ll start by mastering Python’s fundamental building blocks — including variables, strings, numbers, conditionals, loops, and functions — all explained clearly with practical examples.

As you advance, you’ll gain hands-on experience with essential data structures like lists, dictionaries, tuples, and sets, while learning powerful concepts such as comprehensions, lambda functions, and generators to write elegant, Pythonic solutions.

This course also includes carefully crafted coding assignments that mirror common technical interview challenges — from reversing strings and checking prime numbers to merging lists — providing the practice needed to excel in any coding interview.

Later, you’ll dive into object-oriented programming with classes and exception handling, equipping you with the skills to solve intermediate and advanced problems with ease.

To ensure you’re fully prepared, a special section covers LeetCode-style interview problems explained through the perspective of a Google engineer.

Whether your goal is to land your first tech job, automate workflows, or ace coding interviews, this course offers a practical foundation and powerful assignments that will help you succeed with confidence.

Listed below are the concepts you will learn through this first part of the video:

• Variable names

• Strings

• Escape sequences

• Formatted strings

• Check memory address

• String methods

• Numbers - Int, float and complex imaginary

• Working with numbs, round, abs, ceil floor

• Data type conversion

• Comparison operators

• Conditional IF statements

• Ternary operator

• Logical operators

• Short circuit evaluation

• Chaining comparison operators

• Quizz

• For Loops

• Nested Loops

• Iterables

• While Loops

• Quizz

• Defining functions

• Arguments

• Types of functions

• Keyword Arguments

• Default Arguments

• Xargs

• XXargs

• Data structures: lists, tuples, sets and dictionaries

• Accessing items

• List unpacking

• Sorting lists

• Sorting tuples

• Lambda functions

• Map and Zip function

• Filter function

• List Comprehensions

• Tuple Comprehensions

• Generator expressions

• Handling exceptions

• Classes

and also most challenging interview questions to crack the interviews in your dream company!

Learn how to create meaningful variable names, manipulate strings with escape sequences and formatted strings, and explore string methods. Understand numbers including integers, floats, and complex types. Master numerical functions like round, abs, ceil, floor, perform data type conversion, use comparison operators, and write effective conditional IF statements.

Explore the ternary operator for concise conditionals and master logical operators with short circuit evaluation. Learn chaining comparisons for readable code. Practice with a quiz, and dive into for loops, nested loops, and working with iterables to efficiently process collections and control program flow.

Master while loops to execute code repeatedly based on conditions. Test your knowledge with a quiz. Learn how to define functions with various argument types, including keyword and default arguments, and understand different function types to write flexible, reusable, and efficient Python code.

Understand how to use *args and **kwargs for flexible function arguments. Explore core data structures like lists, tuples, sets, and dictionaries, learn to access items, perform list unpacking, and master sorting lists to organize and manipulate data efficiently in Python.

Learn how to sort tuples efficiently and harness the power of lambda functions for concise, anonymous operations. Explore map, zip, and filter functions to process collections, and master list comprehensions for clean, readable, and Pythonic ways to create and transform lists quickly.

Discover tuple comprehensions (using generator expressions), and master generator expressions for memory-efficient data processing. Learn effective exception handling to write robust code, and dive into classes to implement object-oriented programming, enabling you to create reusable, modular, and organized Python programs with custom data structures and behaviors.