What is Data Structure and Algorithm?
A data structure is a method of organizing data in a virtual system. Think of sequences of numbers, or tables of data: these are both well-defined data structures. An algorithm is a sequence of steps executed by a computer that takes an input and transforms it into a target output.
Together, data structures and algorithms combine and allow programmers to build whatever computer programs they’d like. Deep study into data structures and algorithms ensures well-optimized and efficient code.
Common Data Structures and Algorithms
Common data structures you’ll see across different programming languages include:
- Linked lists
- Stacks
- Queues
- Sets
- Maps
- Hash tables
- Search trees
Each of these has its own computational complexity for associated functions like adding items and finding aggregate measures such as the mean for the underlying data structure.
Some common categories of algorithms are:
- Search
- Sorting
- Graph/tree traversing
- Dynamic programming
- Hashing and regex (string pattern matching)
How To Learn Data Structures and Algorithms
- Gradually move beyond HTML/CSS to a programming language: Python is good because it’s versatile and can be used for many programming paradigms, and has more elegant syntax than JavaScript. Eventually, you’ll work towards defining your own data structures and algorithms.
- Get familiar with computational complexity: In particular, Big O notation and the different scales of time and space that represent the worst-case scenarios for your algorithms from input to output, from linear, polynomial, exponential, to logarithmic time scales. These scales will have dramatic differences in the performance and expected computation times of your algorithms. Something that might be logarithmic might scale decently well with large data sets and inputs, while something that is exponential may never finish in time.
- Understand different data structures and algorithm types. Read through basic data structure and algorithm types to get a better feel for the subject.
- Practice: Practice implementing algorithmic principles and actual algorithms and data structures with different exercises. Build your own programs.
- Get on-the-job training. Get a job in software engineering or a role where data structures and algorithms are implemented in order to best exercise your new knowledge.
