 # Data structure & Algorithms for beginners for Data Science

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

Course content
Expand all 171 lectures12:47:27
Introduction
20:03
Preview04:39
Introduction- Part 2 – Data Structure
04:26
Introduction Part 3: Data structure and algorithm
04:17
Introduction Part 4: Data structure and algorithm
01:57
Introduction Part 5: Data structure and algorithm
02:47
Introduction Part 6: Data structure and algorithm
01:57
+Recursion – Data Structures
8 lectures32:23
+Algorithm Run time
7 lectures29:07
+Array – Data structure
3 lectures14:27
+Stack – Data Structure
4 lectures18:41
+Queue – Data Structure
9 lectures42:24
22 lectures01:40:39
+Tree
24 lectures01:25:41
+Binary Search Tree
8 lectures32:44
+AVL Tree
10 lectures39:14
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.

This course contains of these below mentioned topic:

• Recursion.
• Algorithm run time analysis
• Arrays
• Stack
• 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.
Scroll to Top