Algorithms and Data Structures in Python (INTERVIEW Q&A)

Course Feature
  • Cost
    Paid
  • Provider
    Udemy
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    2023-07-04
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Holczer Balazs
Next Course
4.5
27,606 Ratings
This course is perfect for anyone looking to learn the fundamentals of data structures, algorithms and graphs in Python. It covers topics such as setting up the environment, arrays, linked lists, stacks and queues, binary search trees, AVL trees and red-black trees, priority queues and heaps, hashing and dictionaries, graph traversal, shortest path problems, spanning trees, substring search algorithms, Hamiltonian cycles, sorting algorithms and algorithms analysis. Each chapter includes theoretical background and step-by-step code implementation in Python. This course is ideal for those looking to use Python in fields such as investment banking, artificial intelligence or electronic trading algorithms on the stock market. Join now and start learning!
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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 18th, 2023]

This course, Algorithms and Data Structures in Python (INTERVIEW Q&A), is designed to provide an overview of data structures, algorithms and graphs. Students will learn to implement the problems in Python programming language. The course will cover topics such as setting up the environment, differences between data structures and abstract data types, arrays, linked lists, stacks and queues, binary search trees, balanced binary trees (AVL Trees and Red-Black Trees), priority queues and heaps, hashing and dictionaries, graph traversal, shortest path problems (Dijkstra's and Bellman-Ford Algorithms), spanning trees (Kruskal's and Prim's Approaches), substring search algorithms, Hamiltonian cycles (Travelling Salesman Problem), sorting algorithms, and algorithms analysis. Students will gain an understanding of the theoretical background of each algorithm or data structure, and will write the code step by step in Python. This course is beneficial for those interested in fields such as investment banking, artificial intelligence, or electronic trading algorithms on the stock market.

Course Syllabus

Introduction

Installation and Environment Setup

### DATA STRUCTURES ###

Data Structures - Arrays

Interview Questions - (Arrays)

Data Structures - Linked Lists

Data Structures - Doubly Linked Lists

Interview Questions (Linked Lists)

Data Structures - Stacks

Data Structures - Queues

Interview Questions (Stacks and Queues)

Data Structures - Binary Search Trees

Interview Questions (Binary Search Trees)

Data Structures - AVL Trees

Data Structures - Red-Black Trees

Data Structures - Heaps

Interview Questions (Heaps)

Data Structures - Associative Arrays (Dictionaries)

### GRAPH ALGORITHMS ###

Graph Algorithms - Graph Traversal Algorithms

Depth-First Search

Interview Questions (Graph Traversal)

Graph Algorithms - Shortest Paths with Dijkstra's Algorithm

Graph Algorithms - Shortest Paths with Bellman-Ford Algorithm

Interview Questions (Shortest Paths)

Graph Algorithms - Spanning Trees with Kruskal Algorithm

Graph Algorithms - Spanning Trees with Prims Algorithm

Hamiltonian Cycles - Travelling Salesman Problem

### SUBSTRING SEARCH ALGORITHMS ###

### SORTING ALGORITHMS ###

Interview Questions (Sorting)

Other Algorithmic Problems

### APPENDIX - COMPLEXITY THEORY CRASH COURSE ###

Next Steps

Course Materials (DOWNLOADS)

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Pros & Cons
  • Good teaching with clear explanation
  • Visuals and simple explanations
  • Lack of accessibility for newcomers
  • Course structure and content organization
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