Data structure & Algorithms for beginners for Data Science
Learn to master Data structure Algorithmic Programming Techniques. Learn algorithms through concepts and time analysis
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.
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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