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:
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Technical Interview Questions
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Big O Notation
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Stack
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Queue
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Deque
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Arrays
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Linked List
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Heap
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Graph
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Tree
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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
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Codestars • over 2 million students worldwide!
Teaching the Next Generation of Coders -
Atil Samancioglu
Bestselling Instructor
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 2 votes
- 3 stars: 4 votes
- 4 stars: 15 votes
- 5 stars: 27 votes
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