MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 7.5 Hours | Lec: 74 | 1.12 GB | Language: English | Sub: English [Auto-generated]
Backtracking, dynamic programming, Sudoku, knapsack problem, binpacking, closest pair of points, recursion, monte carlo
What you'll learn
Understand backtracking
Understand dynamic programming
Understand recursive approaches
Solve problems from scratch
Requirements
Basic Java
Description
This course is about the fundamental concepts of algorithmic problems, focusing on backtracking and dynamic programming. As far as I am concerned these techniques are very important nowadays, algorithms can be used (and have several applications) in several fields from software engineering to investment banking or R& D.
Section 1:
what are recursion and recursive methods
linear and binary search
tower of Hanoi problem
Section 2:
what are selection algorithms
quickselect algorithm
the secretary problem
Section 3:
what is backtracking
n-queens problem and Hamiltonian cycle problem
knight's tour problem
Sudoku game
Section 4:
what is dynamic programming
knapsack problem
coin change problem and rod cutting problem
Section 5:
bin packing problem
closest pair of points problem
Section 6:
top interview questions (Google, Facebook and Amazon)
The first chapter is about backtracking: we will talk about problems such as n-queens problem or hamiltonian cycles, coloring problem and Sudoku problem. In the second chapter we will talk about dynamic programming, theory then the concrete examples one by one: fibonacci sequence problem and knapsack problem.
In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together from scratch in Java.
FINALLY YOU CAN LEARN ABOUT THE MOST COMMON INTERVIEW QUESTIONS (Google, MicroSoft, EPAM etc.)
Thanks for joining the course, let's get started!
Who this course is for?
This course is meant for newbies who are not familiar with algorithmic problems in the main or students looking for some refresher
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