Learn dynamic programming with online courses
What is dynamic programming (DP)?
Dynamic programming involves breaking down significant programming problems into smaller subsets and creating individual solutions. It's an integral part of building computer solutions for programming. The technique of dynamic programming takes optimization problems and divides them into simpler subproblems, storing solutions so programmers only solve each smaller problem once. When done correctly, the solutions build on each other to create an optimal solution for the original question, helping users avoid overlap and re-coding for similar issues within the problem framework.¹
Dynamic programming solutions make use of these overlapping subproblems to facilitate solving the original issue. It reduces the number of binary search trees within an algorithm and can help mitigate greedy algorithms. A typical example would be the Floyd-Warshall algorithm, a method for finding the shortest path in a weighted graph, an algorithm designed in the 1960s.² It allows programmers, developers, and coders to edit distance and increase the number of ways to solve an issue within a broader context.
Browse online Dynamic Programming courses
Stand out in your fieldUse the knowledge and skills you have gained to drive impact at work and grow your career.
Learn at your own paceOn your computer, tablet or phone, online courses make learning flexible to fit your busy life.
Earn a valuable credentialShowcase your key skills and valuable knowledge.
Solve different types of dynamic programming problems
By solving dynamic programming problems, coders can create shorter paths to solutions in their coding. Taking a bottom-up approach, dynamic programming can avoid the memory cost of recursion algorithms by reducing the maximum number of decision trees a program has to create to solve.
Examples of dynamic programming problems include:
The longest common subsequence problem, which involves finding the longest subsequence common to all sequences in a given set of sequences.
The matrix-chain multiplication problem, in which coders find the most efficient solution for multiplying a given sequence of matrices.
The knapsack problem, in which, given a set of restraints, coders must find an optimal solution.
Explore dynamic programming jobs
Learning dynamic programming can help those looking to pursue computer programming and software development occupations. To work in these fields, individuals may need to earn a bachelor’s degree or a master’s degree in computer science or a related field.³, ⁴ Salaries for computer programmers and software developers vary based on position, level of experience, location, and other factors. However, these occupations can offer competitive compensation.⁵
How to become a dynamic programmer online
In addition to exploring a coding boot camp, a bachelor’s in computer and data science degree, or a master’s in data science, aspiring dynamic programming professionals may consider other learning opportunities, such as dynamic programming certificates and similar credentials.
Problem-solving skills are useful to computer programming and software development careers. In a job interview, a candidate may be asked to find solutions for dynamic programming problems. Online programming courses can help job seekers prepare. Searching for dynamic programming tutorials may also help.