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- Part 2 – Data Structure
Introduction Part 3: Data structure and algorithm
Introduction Part 4: Data structure and algorithm
Introduction Part 5: Data structure and algorithm
Introduction Part 6: Data structure and algorithm
+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
+Linked List
22 lectures01:40:39
24 lectures01:25:41
+Binary Search Tree
8 lectures32:44
+AVL Tree
10 lectures39:14
  • Basic computer programming
  • Basic Mathematics knowledge

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
  • 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.

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