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Lane Wagner
Instructor
Lane is a back-end engineer and the lead instructor of Boot.dev. He has taught over one million students worldwide, on Boot.dev, FreeCodeCamp, YouTube and the Backend Banter podcast. Lane worked as a backend engineer writing Go, Python and TypeScript, then moved into engineering management and a couple of years later left to build Boot.dev full-time.
Completion
Certificate included
Format
Interactive coding
Freemium
Build data structures from scratch in Python
Analyze algorithms using Big-O notation
Implement sorting algorithms for efficient data handling
Create and manipulate stacks and queues
Develop binary trees and understand their applications
If you've had trouble getting past a hard whiteboarding session, this course is for you. Big-O complexity is arguably the most important concept students learn in a formal computer science degree. You'll build data structures from scratch in Python and improve your problem-solving skills. We'll cover binary trees, linked lists, stacks, graphs and more. This Python course will give you the foundation you need to start your career off on the right foot. After completing this course, you'll be comfortable crushing interview questions and writing performant code.
Learn about what algorithms are and why they matter
Learn the math required to understand Big-O notation, namely exponents, logarithms, and factorials
Figure out what Big-O notation and time complexity mean in the context of algorithms and performant code
Learn how data is sorted on a computer, and how to sort it faster
Understand why exponential time complexity is so dangerous
Learn about data structures and how they play a critical role in algorithms
Learn about stacks, the original LIFO data structure and build one from scratch
Learn about the FIFO queue data structure and how to implement a simple one from scratch
Understand how linked lists vary from arrays and how to use one to build a faster queue
Learn about binary trees, what they are used for, and implement one from scratch
Solve the classic balancing problem of traditional binary trees with a red-black algorithm
Build a hashmap from scratch and learn how to use the Python dictionary type effectively
Build all the methods of a trie class, and efficiently search entire documents of text
Learn about graph structures and how we can use them to quickly solve a wide array of search problems
Implement and understand the ever-famous breadth first and depth-first search algorithms
Learn about P and NP
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