What you'll learn

Apply basic algorithmic techniques such as greedy algorithms, binary search, sorting and dynamic programming to solve programming challenges.
Apply various data structures such as stack, queue, hash table, priority queue, binary search tree, graph and string to solve programming challenges.
Apply graph and string algorithms to solve real-world challenges: finding shortest paths
Solve complex programming challenges using advanced techniques


Requirements

Basic computer programming
Basic Mathematics knowledge

Description

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.

You will learn a lot of theory: how to sort data and how it helps for searching. How to break a large problem into pieces and solve them recursively and it makes sense to proceed greedily.

Implemented all the concepts using Python using Pycharm IDE and explained the time complexity and difficulty of the data structures.

This course contains of these below mentioned topic:

Recursion.

Algorithm run time analysis

Arrays

Stack

Linked list

Data Structure

Binary Tree

Binary Search Tree

AVL Tree

Heap tree

Queue

Sorting

Hash Table

Graph Theory

Magic Framework

Computer Programming

Dynamic Programming

Who this course is for:

Beginner who have little programming experience , willing to learn and pursue data science career.

Homepage: https://www.udemy.com/course/data-structure-algorithms-for-beginners-for-data-science/

Download Part 01

Download Part 02

Download Part 03

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