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Autor Tópico: Algorithms in Python : Design Techniques And Approach  (Lida 106 vezes)

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Offline mitsumi

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Algorithms in Python : Design Techniques And Approach
« em: 03 de Março de 2021, 11:23 »

Algorithms in Python : Design Techniques And Approach
Duration: 17h35m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.95 GB
Genre: eLearning | Language: English
BackTracking,Divide & Conquer,Dynamic Programming,Greedy Algorithms via Data Structures for Interview & problem solving

What you'll learn
Algorithms In Python
Algorithms Design Techniques
Data Structures
Tress
Graphs
Dynamic Programming , Recursion, Backtracking

Requirements
Basic Python
Description
Algorithm Design Techniques: Live problem-solving in Python

Algorithms are everywhere. One great algorithm applied sensibly can result in a System like GOOGLE!

Completer scientists have worked for 100s of years and derived some of the techniques that can be applied to write and design algorithms.

So Why to reinvent the wheel ??

Let's go through some of the most famous algorithm design techniques in this course.

Once you will come to know these design techniques It will become very easy for you to approach a problem by identifying which technique to apply to solve that correctly and efficiently.

0. Complexity analysis

1. Recursion is the base of any algorithm design

2. Backtracking

3. Divide and Conquer

4. Greedy algorithms

5. Dynamic programming

6. Trees

7. Graphs

And WE WILL WRITE THE CODE LINE BY LINE IN PYTHON !!

By the end of this course -

1. You will understand how to design algorithms

2. A lot of coding practice and design live problems in Java

3. Algorithm Complexity analysis

AND

If you are preparing for your coding Interview or doing competitive programming This course will be a big help for you.

THRILLED? I welcome you to the course and I am sure this will be fun!!

If it does not - It comes with a 30 Days money-back guarantee so don't think twice to give it a shot.

Happy Learning

Basics>Strong;

Who this course is for:
Want to Learn to Design Algorithms

Download link:
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