Mastering critical SKILLS in Algorithms using C++- Part 2

Mastering critical SKILLS in Algorithms using C++: Part 2, available at $84.99, has an average rating of 4.89, with 135 lectures, based on 216 reviews, and has 2565 subscribers.

You will learn about Master recursive techniques by solving MANY problems Expose yourself to many algorithmic techniques After the course, a smooth experience to prepare for coding interviews Short and well written codes This course is ideal for individuals who are People who want to master a critical CS component or People who want to prepare for interviews, then Algorithms is a must step before interviews preparations It is particularly useful for People who want to master a critical CS component or People who want to prepare for interviews, then Algorithms is a must step before interviews preparations.

Enroll now: Mastering critical SKILLS in Algorithms using C++: Part 2

Summary

Title: Mastering critical SKILLS in Algorithms using C++: Part 2

Price: $84.99

Average Rating: 4.89

Number of Lectures: 135

Number of Published Lectures: 135

Number of Curriculum Items: 135

Number of Published Curriculum Objects: 135

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Master recursive techniques by solving MANY problems

Expose yourself to many algorithmic techniques

After the course, a smooth experience to prepare for coding interviews

Short and well written codes

Who Should Attend

People who want to master a critical CS component

People who want to prepare for interviews, then Algorithms is a must step before interviews preparations

Target Audiences

People who want to master a critical CS component

People who want to prepare for interviews, then Algorithms is a must step before interviews preparations

Almost all other courses focus on knowledge. In this course, we focus ongaining real skills.

Overall:

The course covers a good subset of algorthmic topics

Learn the inner details of the algorithms and their time & memory complexity analysis

Learn how to code line-by-line

Source code and Slides and provided for all content

An extensive amount of practice to master the taught algorithms (where most other content fails!)

Content:

Dynamic Programming: Intro

DP: Pick or Leave Pattern

DP: Enumerating the choices

DP Range Patterns

DP on Graph and Grids

DP Counting

DP: Printing Solution

DP Tabulation

DP Solving Marathon

Backtracking

Divide and Conquer

Shortest Path Algorithm: Floyd-Warshal

Shortest Path Algorithm: Bellman-Ford

Shortest Path Algorithm: Dijkstra

Minimum Spanning Tree: Prim

Minimum Spanning Tree: Kruskal

Teaching Style:

Instead of long theory then coding style, we follow a unique style

I parallelize the concepts with the codes as much as possible

Unless better for you to work on pseudocode first

Go Concrete as possible

Use Clear Simple Visualization

Engagement

By the end of the journey

Solid understanding of Algorithms topics in C++

Mastering different skills

Analytical and Problem-Solving skills

Clean coding for algorithms

With the administered problem-solving skills

You can start competitive programming smoothly

A strong step toward interviews preparation

Prerequisites

Programming Skills:

Strong Programming skills

Solving a lot of basic problem-solving problems on fundamentals

Good understanding for basic recursion (E.g. Fibonacci)

STL, especially Vectors, map/set, unordered map/set

Highly Preferred: 

Do programming projects

Finish a descent data structure course (extensive data structure practice)

Don’t miss such a unique learning experience!

Acknowledgement: “I’d like to extend my gratitude towards Robert Bogan for his help with proofreading the slides for this course”

Course Curriculum

Chapter 1: Dynamic Programming (DP) – Intro

Lecture 1: Fibonacci Sequence

Lecture 2: Fibonacci RCA

Lecture 3: Fibonacci Implementations

Lecture 4: Dynamic Programming

Chapter 2: DP: Pick or Leave Pattern

Lecture 1: Knapsack Problem 1

Lecture 2: Knapsack Problem 2

Lecture 3: Knapsack Problem 3

Lecture 4: Knapsack Problem 4

Lecture 5: Knapsack Problem 5

Lecture 6: LIS Problem 1

Lecture 7: LIS Problem 2

Lecture 8: LIS Problem 3

Lecture 9: LIS Problem 4

Lecture 10: LCS Problem 1

Lecture 11: LCS Problem 2

Lecture 12: DP homework 1 – 3 Medium Challenges

Lecture 13: DP homework 1 – Solutions p1 p2

Lecture 14: DP homework 1 – Solutions p3

Lecture 15: DP homework 2 – 3 Medium to Hard Challenges

Lecture 16: DP homework 2 – Solutions p1

Lecture 17: DP homework 2 – Solutions p2

Lecture 18: DP homework 2 – Solutions p3

Chapter 3: DP: Enumerating the choices

Lecture 1: Edit Distance 1

Lecture 2: Edit Distance 2

Lecture 3: Integer Break 1

Lecture 4: Integer Break 2

Lecture 5: DP Homework 1 – 2 Easy to Medium Challenges

Lecture 6: DP Homework 1 – Solutions

Chapter 4: DP: Range Patterns

Lecture 1: General Range Pattern

Lecture 2: Consecutive Range Pattern

Lecture 3: Nested Range Pattern 1

Lecture 4: Nested Range Pattern 2

Lecture 5: DP Homework 1 – 3 Medium Challenges

Lecture 6: DP Homework 1 – Solutions

Lecture 7: DP Homework 2 – 2 Hard Challenges

Lecture 8: DP Homework 2 – Solutions

Chapter 5: DP: Counting

Lecture 1: Counting DP 1

Lecture 2: Counting DP 2

Lecture 3: DP Homework 1 – 4 Medium Challenges

Lecture 4: DP Homework 1 – Solutions p1

Lecture 5: DP Homework 1 – Solutions p2

Lecture 6: DP Homework 1 – Solutions p3

Lecture 7: DP Homework 1 – Solutions p4

Chapter 6: DP on Grid

Lecture 1: DP on Grid

Lecture 2: DP on Grid Homework 1 – 4 Medium to Hard Challenges

Lecture 3: DP on Grid Homework 1 – Solutions p1 p2

Lecture 4: DP on Grid Homework 1 – Solutions p3

Lecture 5: DP on Grid Homework 1 – Solutions p4

Chapter 7: DP: Building Output

Lecture 1: Building DP Output

Lecture 2: Building DP Output Homework 1 – 3 Medium Challenges

Lecture 3: Building DP Output Homework 1 – Solutions

Chapter 8: DP Tablulation

Lecture 1: Note

Lecture 2: DP Tabulation

Lecture 3: LIS Tabulation 1A

Lecture 4: LIS Tabulation 1B

Lecture 5: LIS Tabulation 2

Lecture 6: Coin Change Tabulation 1

Lecture 7: Coin Change Tabulation 2

Lecture 8: DP Tabulation Homework 1 – 4 Easy to Medium Challenges

Lecture 9: DP Tabulation Homework 1 – solutions

Lecture 10: DP Tabulation Homework 2 – 3 Very Hard Challenges [Optional]

Chapter 9: DP Marathon

Lecture 1: More to tackle

Chapter 10: Backtracking

Lecture 1: Backtracking 1

Lecture 2: Backtracking 2 – Maze

Lecture 3: Backtracking 3 – Maze Tracing

Lecture 4: Backtracking 4 – Maze Extension

Lecture 5: Backtracking – Partition to K 1

Lecture 6: Backtracking – Partition to K 2

Lecture 7: Backtracking – Partition to K 3

Lecture 8: Backtracking – Partition to K 4

Lecture 9: Backtrack Homework 1 – 6 Medium to Hard Challenges

Lecture 10: Backtrack Homework 1 – Solution p1

Lecture 11: Backtrack Homework 1 – Solution p2

Lecture 12: Backtrack Homework 1 – Solution p3

Lecture 13: Backtrack Homework 1 – Solution p4

Lecture 14: Backtrack Homework 1 – Solution p5

Lecture 15: Backtrack Homework 1 – Solution p6

Chapter 11: Divide and Conquer

Lecture 1: Divide and Conquer Algorithm

Lecture 2: Merge Sort Code

Lecture 3: Merge Sort Complexity

Lecture 4: Quicksort 1

Lecture 5: Quicksort 2 Code

Lecture 6: Quicksort 3 Complexity

Lecture 7: More on Complexity

Lecture 8: DC Homework – 5 Medium Challenges

Lecture 9: DC Homework – solutions

Chapter 12: Graph: Shortest Path – Floyd-Warshall

Lecture 1: Shortest Path Algorithms

Lecture 2: Floyd-Warshall Algorithm 1 – The Challenge

Instructors

CSkilled Academy
High Quality With Intensive Practice CS Courses

Dr. Moustafa Saad Ibrahim
Educator, Software Engineer, Scientist, Competitive Coach

Rating Distribution

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2 stars: 0 votes

3 stars: 2 votes

4 stars: 11 votes

5 stars: 203 votes

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