Complete Data Structures and Algorithms- Software Interviews

Complete Data Structures and Algorithms: Software Interviews, available at $64.99, has an average rating of 4.4, with 148 lectures, based on 48 reviews, and has 1532 subscribers.

You will learn about Data Structures Algorithms Technical Interview Question Solutions Python This course is ideal for individuals who are Programmers trying to land a job in big technology companies or Programmers looking forward to improve their coding skills or Programmers looking to learn about data structures & algorithms It is particularly useful for Programmers trying to land a job in big technology companies or Programmers looking forward to improve their coding skills or Programmers looking to learn about data structures & algorithms.

Enroll now: Complete Data Structures and Algorithms: Software Interviews

Summary

Title: Complete Data Structures and Algorithms: Software Interviews

Price: $64.99

Average Rating: 4.4

Number of Lectures: 148

Number of Published Lectures: 148

Number of Curriculum Items: 148

Number of Published Curriculum Objects: 148

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Data Structures

Algorithms

Technical Interview Question Solutions

Python

Who Should Attend

Programmers trying to land a job in big technology companies

Programmers looking forward to improve their coding skills

Programmers looking to learn about data structures & algorithms

Target Audiences

Programmers trying to land a job in big technology companies

Programmers looking forward to improve their coding skills

Programmers looking to learn about data structures & algorithms

Welcome to the Complete Data Structure & Algorithms: Technical Interviews course

Data structures and algorithms is not just a subject which every programmer should master but also a major topic in technical interviews by giant technology companies such as Google, Amazon, Microsoft, Netflix, Uber, Tesla etc.

Not only we will learn about the theory and practical implementations of the data structures & algorithms but also we will solve many technical interview questions and practice what we learn in each section.

During the course we will use Python programming language for all implementations and question solutions. However if you are sufficient in any other programming language before, you would be fine. We have a quick Python Refresher section where you can learn about the fundamentals if you want to adapt. Alternatively you can learn all the algorithms and solutions and implement them in your own preferred language as well.

This course is brought to you by Atil Samancioglu, teaching more than 300.000 students worldwide on programming and cyber security along with the Codestars, serving more than 1 million students! Atil also teaches mobile application development in Bogazici University and he is founder of his own training startup Academy Club.

Some of the topics that will be covered during the course:

Technical Interview Questions

Big O Notation

Stack

Queue

Deque

Arrays

Linked List

Heap

Graph

Tree

HashTable

After you complete the course you will be able to solve technical interview questions, improve your programming skills and implement ideas in real life problems. You will be given many opportunities to solve questions on your own during the training and it will be vital for you to follow these instructions.

If you are ready, let’s get started!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Course Outline

Chapter 2: Big O Notation

Lecture 1: Big O Introduction

Lecture 2: What is Big O?

Lecture 3: Big O Code Examples

Lecture 4: Space Complexity

Lecture 5: Big O GitHub Link

Chapter 3: Lists & Arrays

Lecture 1: Lists Introduction

Lecture 2: Arrays 101

Lecture 3: Lists

Lecture 4: Arrays & Lists GitHub Link

Lecture 5: Contains Duplicate

Lecture 6: Contains Duplicate Solution

Lecture 7: Contains Duplicate GitHub Link

Lecture 8: Find Single

Lecture 9: Single Number Solution

Lecture 10: Find Single GitHub Link

Lecture 11: Majority Element

Lecture 12: Boyer Moore

Lecture 13: Majority Element GitHub Link

Chapter 4: Stack, Queue & Deque

Lecture 1: Stack, Queue, Deque Introduction

Lecture 2: What is Stack, Queue, Deque?

Lecture 3: LifoQueue

Lecture 4: Stack Implementation

Lecture 5: Queue Implementation

Lecture 6: Deque Implementation

Lecture 7: Stack, Queue, Deque GitHub Link

Lecture 8: Implement Stack Using Queue

Lecture 9: Writing the Stack

Lecture 10: Implement Stack GitHub Link

Lecture 11: Baseball Game

Lecture 12: Baseball Solution

Lecture 13: Baseball GitHub Link

Lecture 14: Daily Temperatures

Lecture 15: Daily Temperatures Solution

Lecture 16: Daily Temperatures GitHub Link

Chapter 5: Linked List

Lecture 1: Linked List Introduction

Lecture 2: What is Linked List?

Lecture 3: Doubly Linked List

Lecture 4: Linked List O Notation

Lecture 5: Linked List GitHub Link

Lecture 6: Remove nth Node

Lecture 7: Remove nth Node Solution

Lecture 8: Remove nth Node GitHub Link

Lecture 9: Linked List Intersection

Lecture 10: Intersection Solution

Lecture 11: Intersection GitHub Link

Lecture 12: Duplicate

Lecture 13: Floyd

Lecture 14: Duplicate GitHub Link

Chapter 6: Tree

Lecture 1: Tree Introduction

Lecture 2: What is Tree?

Lecture 3: Tree Big O Notation

Lecture 4: Insert Method

Lecture 5: Finishing BST

Lecture 6: Tree GitHub Link

Lecture 7: Recursion

Lecture 8: Recursion GitHub Link

Lecture 9: Reverse String

Lecture 10: Reverse String Recursion

Lecture 11: Reverse String GitHub Link

Lecture 12: Fibonacci

Lecture 13: Recursion vs Iteration

Lecture 14: Memoization

Lecture 15: Fibonacci GitHub Link

Lecture 16: Invert Binary Tree

Lecture 17: Invert Tree Solution

Lecture 18: Invert Binary GitHub Link

Chapter 7: Tree Traversal

Lecture 1: Tree Traversal Introduction

Lecture 2: BFS vs DFS

Lecture 3: BFS Implementation

Lecture 4: DFS Implementation

Lecture 5: DFS Other Methods

Lecture 6: Tree Traversal GitHub Link

Lecture 7: BST to Tree

Lecture 8: DFS Solution

Lecture 9: Greater BST GitHub Link

Lecture 10: Binary Tree Max Path Sum

Lecture 11: DFS Returning Solution

Lecture 12: Binary Tree Max GitHub Link

Chapter 8: Graph

Lecture 1: Graph Introduction

Lecture 2: What is Graph?

Lecture 3: Graph Implementation

Lecture 4: Graph GitHub Link

Lecture 5: Reorder Routes

Lecture 6: DFS Solution

Lecture 7: Reorder Routes GitHub Link

Lecture 8: Number of Islands

Lecture 9: BFS Solution

Lecture 10: Number of Islands GitHub Link

Lecture 11: Redundant Connection

Lecture 12: Union Find

Instructors

Codestars ? over 2 million students worldwide!
Teaching the Next Generation of Coders

Atil Samancioglu
Bestselling Instructor

Rating Distribution

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2 stars: 2 votes

3 stars: 4 votes

4 stars: 15 votes

5 stars: 27 votes

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