How to Learn Data Structures and Algorithms: A Basic Guide

Data structures and algorithms (DSA) are a discipline within computer science that creates the building blocks for solving problems in computer programming and algorithmic design. For this reason, understanding data structures and algorithms is a fundamental skill critical for programmers and computer scientists to use in developing efficient programs. 

Niklaus Wirth, a Swiss computer scientist who created the programming languages Pascal and Modula, summarized how DSA works by the title of his 1976 book Algorithms + Data Structures  = Programs. This formulation shows the inherent relation the data structures and algorithms have with each other and how they work together to create computer programs. Learning about DSA is essential to understanding how computers and programs work so that you can effectively manipulate them when designing programs.

What are data structures and algorithms?

Data structures and algorithms are tools for working with abstract data types (ADT). These ADTs are values or parts that only work with specific operations within a programming language. Some ADTs include integers, floats, Booleans, and strings; however, an ADT can also be a more complex data type, such as colors, images, and user-created objects. On a computer, data structures represent the values and operations of an ADT:

• Data structure: A representation of an abstract data type meant for storage and retrieval 

Learning about DSA is learning how to manipulate ADTs on a computer using data structures given to the ADT. To define the manipulation of ADTs, you use an algorithm:

• Algorithm: A series of finite instructions within a program that dictate computations

Algorithms solve problems in a computer program by their design, intention, implementation, and data structures. 

Why do data structures and algorithms go together?

Data structures and algorithms go together because algorithms dictate the series of manipulations data structures go through to solve problems through computations. If ADTs dictate the values and their operations, data structures put those entities into a form that an algorithm performs computations on within a program. 

Why is the study of data structures and algorithms important?

Studying data structures and algorithms is critical to developing efficient computer science problem-solving skills. Every program combines data structures and algorithms, so studying DSA gives computer programmers a collection of them to understand and use in their programs. It also teaches you how to use common and effective data structures and algorithms. 

Every data structure and algorithm has certain costs and benefits. One algorithm might be effective for the program but may require lots of processing power or memory. So, studying DSA helps you weigh which algorithms are best for specific situations. Understanding how effective a particular data structure and algorithm is essential when you create your own and need to know how efficient it is. 

Fundamental aspects of data structures and algorithms

Learning the commonly used data structures and algorithms, including how they work, when to use them, and the benefits and tradeoffs they each provide, is the basic building block of learning them. It’s also important to understand how different programming languages implement data structures and algorithms. Although DSAs are antagonistic to programming languages, each language uses them differently. 

Learn how to implement data structures to solve problems. 

Implementing data structures to solve problems is vital in writing a program. To do this, you must understand the kinds of data structures available and how they work. A systematic approach to this includes:

1. Understand your problem and the operations that insert, delete, and find data within the structure. 

2. Find the most efficient path to implementing each data operation needed.

3. Pick a data structure best suited for your needs with each constraint known and your operations determined. 

Learning to ask specific data structure questions leads to determining the most effective. Some questions in line with the systematic framework include:

• Do you need to constantly change, delete, and insert information into the data structure?

• Does the order of items in the structure matter?

• How often does the structure need sorting?

• How is the structure accessed? Through a neat table or random access?

You must learn about specific data structures to analyze them systematically and decide which one to use.

Explore classic data structures

There are hundreds of types of data structures. Some of the classic ones include:

• Array

• Linked List

• Stack

• Queue

• Tree

• Hash table

Learn how to analyze algorithms.

Algorithm analysis is crucial in learning how algorithms work and when one algorithm is more efficient or better at solving a problem than another. Like data structures, some algorithms take more memory and processing to complete a task than others. One way to do this is to have a process that analyzes the algorithm's efficiency, taking the input size (often determined by the data structure) into account and the operation within the algorithm you want to count.

Explore the classic algorithms

Many algorithms exist worldwide, and choosing the right one for your problem combines creative thinking and analysis. Some classic algorithms to explore include:

• Sorting

• Searching

• Graph traversal

• Recursive

• Dynamic programming

How to learn DSA

Since DSA is vital in creating efficient programs, let’s look at some steps to learn DSA to improve or build your skills as a programmer and software engineer. The following list offers some basic steps you can take to develop your DSA skills:

1. Learn DSA for programming languages like Python, C++, Javascript, etc.  

2. Build a knowledge base of the classic data structures and algorithms.

3. Test yourself with practice problems, increasing in difficulty as you master easier ones. 

4. Take courses in DSA, especially if you are already in a computer science program. 

5. Study textbooks on DSA for your language or in general. 

6. Enroll in an online course or certificate program, such as Python Data Structures, from the University of Michigan, available on Coursera.

Getting started on Coursera

Learning data structures and algorithms is fundamental for creating efficient programs and improving your programming skills. They are crucial to building data structures and working with specific algorithms that effectively use data structures. Try the Data Structures and Algorithms Specialization from the University of California San Diego on Coursera to build these skills. This six-course series presents you with programming challenges, algorithm puzzles, and high-level learning material.