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Dynamic Programming Algorithms Master Course (2022)
Ultimate Specialisation on Recursion, Backtracking and Dynamic Programming for Competitive Coding & Interviews.
Created by Apaar Kamal, offered on Udemy
To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 1899 students which left 107 reviews at an average rating of 4.33, which is average.
We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 44 hours 25 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 5 hours 59 minutes.
This course currently has a bestcourses score of 5.6/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.
Are you feeling brushed-up with data structures and algorithms but often feel stuck when it comes to DP! But no more, we are super happy to present the Dynamic Programming Specialisation Course for everyone, to help you master the important Dynamic Programming Concepts and level up for Competitive Coding & Interviews.
The Dynamic Programming Master Course is taught by Apaar Kamal, software engineer at Google & Master on Codeforces along with Prateek Narang, an ex-Google engineer and founder of Coding Minutes. This highly detailed & rigorous curriculum has been designed to ensure your success in online competitions where Dynamic Programming problems are very common these days.
Many top companies like Google, Facebook, Amazon, Directi, CodeNation, Goldman Sachs etc encourage Competitive Programming and conduct coding competitions to hire smart people who can solve problems.
Dynamic Programming is a popular algorithmic technique in computer programming that helps to efficiently solve a class of problems that have overlapping subproblems and optimal substructure property.
If any problem can be divided into subproblems, which in turn are divided into smaller subproblems, and if there are overlapping among these subproblems, then the solutions to these subproblems can be saved for future reference. In this way, algorithm can be improved, and lot of problems can be optimised using Dynamic Programming.
The 40+ hours course covers the breadth & depth of dynamic programming starting from a recap of recursion, backtracking, and diving deep into Dynamic Programming techniques like -
1D, 2D, Multi-dimensional DP
DP and Partition Problems
DP for Combinatorics & Subsequences
DP on Strings
DP on Trees & Graphs
SOS DP and
DP with Bitmasks
DP and Matrix Exponentiation
DP in Game Theory
DP with advanced data structures
[Extra] You will also get Full Solved Atcoder Educational DP Contest as part of the course.
* Detailed video explanations
* Deep dive into advanced DP Concepts
* Carefully curated practice problem sheets
* Full Life Time Access
* All variants of DP Covered
So, what are you waiting for - join the course now and level-up your DP Skills! *
What you will learn
- Identify what type of problems can be solved using DP
- Come with recurrence for most DP Problems
- Master the advance DP techniques
- Face interviews and online challenges more confidently
- Basic understanding of algorithms
- Ability to write/understand code in programming language
- Familiarity with Arrays, 2D Arrays, Data Structures