Computer Science: Programming with a Purpose (Coursera)

Offered by Princeton University,
Computer Science: Programming with a Purpose (Coursera)

The basis for education in the last millennium was “reading, writing, and arithmetic;” now it is reading, writing, and computing. Learning to program is an essential part of the education of every student, not just in the sciences and engineering, but in the arts, social sciences, and humanities, as well. Beyond direct applications, it is the first step in understanding the nature of computer science’s undeniable impact on the modern world.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course covers the first half of our book Computer Science: An Interdisciplinary Approach (the second half is covered in our Coursera course Computer Science: Algorithms, Theory, and Machines). Our intent is to teach programming to those who need or want to learn it, in a scientific context.
We begin by introducing basic programming elements such as variables, conditionals, loops, arrays, and I/O. Next, we turn to functions, introducing key concepts such as recursion, modular programming, and code reuse. Then, we present a modern introduction to object-oriented programming.
We use the Java programming language and teach basic skills for computational problem solving that are applicable in many modern computing environments. Proficiency in Java is a goal, but we focus on fundamental concepts in programming, not Java per se.
All the features of this course are available for free. It does not offer a certificate upon completion.

Syllabus

WEEK 1
Basic programming concepts
Why program? This lecture addresses that basic question. Then it describes the anatomy of your first program and the process of developing a program in Java using either virtual terminals or a program development environment, with some historical context. Most of the lecture is devoted to a thorough coverage of Java's built-in data types, with example programs for each.

WEEK 2
Conditionals and loops
The if, while, and for statements are Java's fundamental control structures. This lecture is built around short programs that use these constructs to address important computational tasks. Examples include sorting, computing the square root, factoring, and simulating a random process. The lecture concludes with a detailed example illustrating the process of debugging a program.

WEEK 3
Arrays
Computing with a large sequence of values of the same type is extremely common. This lecture describes Java's built-in array data structure that supports such applications, with several examples, including shuffling a deck of cards, the coupon collector test for randomness, and random walks in a grid.

WEEK 4
Input and output
To interact with our programs, we need mechanisms for taking information from the outside world and for presenting information to the outside world. This lecture describes several such mechanisms: for text, drawings, and animation. Detailed examples covered include fractal drawings that model natural phenomena and an animation of a ball bouncing around in the display window.

WEEK 5
Functions and libraries
Modular programming is the art and science of breaking a program into pieces that can be individually developed. This lecture introduces functions (Java methods), a fundamental mechanism that enables modular programming. Motivating examples include functions for the classic Gaussian distribution and an application that creates digital music.

WEEK 6
Recursion
A recursive function is one that calls itself. This lecture introduces the concept by treating in detail the ruler function and (related) classic examples, including the Towers of Hanoi puzzle, the H-tree, and simple models of the real world based on recursion. We show a common pitfall in the use of recursion, and a simple way to avoid it, which introduces a different (related) programming paradigm known as dynamic programming.

WEEK 7
Performance
When you develop a program, you need to be aware of its resource requirements. In this lecture, we describe a scientific approach to understanding performance, where we develop mathematical models describing the running time our programs and then run empirical tests to validate them. Eventually we come to a simple and effective approach that you can use to predict the running time of your own programs that involve significant amounts of computation.

WEEK 8
Abstract data types
In Java, you can create your own data types and use them in your programs. In this and the next lecture, we show how this ability allows us to view our programs as abstract representations of real-world concepts. First we show the mechanics of writing client programs that use data types. Our examples involve abstractions such as color, images, and genes. This style of programming is known as object-oriented programming because our programs manipulate objects, which hold data type values.

WEEK 9
Creating data types
Creating your own data types is the central activity in modern Java programming. This lecture covers the mechanics (instance variables, constructors, instance methods, and test clients) and then develops several examples, culminating in a program that uses a quintessential mathematical abstraction (complex numbers) to create visual representations of the famous Mandelbrot set.

WEEK 10
Programming languages
We conclude the course with an overview of important issues surrounding programming languages. To convince you that your knowledge of Java will enable you to learn other programming languages, we show implementations of a typical program in C, C++, Python, and Matlab. We describe important differences among these languages and address fundamental issues, such as garbage collection, type checking, object oriented programming, and functional programming with some brief historical context.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Effective Programming in Scala (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Effective Programming in Scala (Coursera)

Scala is an expressive, versatile, and safe programming language. In this course, you will learn how to get the most out of Scala to solve common programming tasks such as modeling business domains, breaking down complex problems into simpler problems, manipulating data, or running parallel tasks. Along the journey, you will also learn the best practices for writing high-quality code that scales to large applications, how to handle errors, how to write tests, and how to leverage a productive development environment.

Sep 28th 2026
5-12 Weeks
Rebo-binario (Coursera) Coursera
Universidad Autónoma Metropolitana

Rebo-binario (Coursera)

Te damos la bienvenida al curso en línea Rebo-binario, un curso diseñado para incentivar el desarrollo de habilidades mentales relacionados al pensamiento computacional y creativo para la resolución de problemas y la reflexión crítica. Para lograr este cometido echamos mano de estrategias del pensamiento computacional y la creatividad como saberes para el uso y apropiación de herramientas digitales y tecnologías informáticas.

Sep 28th 2026
3 Weeks
Decision Making and Reinforcement Learning (Coursera) Coursera
Columbia University

Decision Making and Reinforcement Learning (Coursera)

This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods.

Sep 28th 2026
5-12 Weeks
Client Needs and Software Requirements (Coursera) Coursera
University of Alberta

Client Needs and Software Requirements (Coursera)

This course covers practical techniques to elicit and express software requirements from client interactions. Upon successful completion of this course, you will be able to: Create clear requirements to drive effective software development; visualize client needs using low-fidelity prototypes; maximize the effectiveness of client interactions - adapt to changing product requirements.

Sep 28th 2026
4 Weeks
Learn CSS Flexbox (Coursera) Coursera
Scrimba

Learn CSS Flexbox (Coursera)

Mastering CSS Flexbox: Unlock the Power of Flexible Web Layouts. Discover the indispensable art of CSS Flexbox and elevate your web development prowess to new heights. In this comprehensive course, you'll gain proficiency in harnessing the unparalleled capabilities of Flexbox, revolutionizing the way you construct websites.

Sep 28th 2026
1 Week
Introduction to Software Product Management (Coursera) Coursera
University of Alberta

Introduction to Software Product Management (Coursera)

This course highlights the importance and role of software product management. It also provides an overview of the specialization, as well as its goals, structure, and expectations. The course explains the value of process, requirements, planning, and monitoring in producing better software. Upon successful completion of this course, you will be able to: relate software product management to better software products; recognize the role of a software product manager; reflect on how Agile principles will improve your own projects.

Sep 28th 2026
2 Weeks
Introducción a UML (Coursera) Coursera
Universidad de los Andes

Introducción a UML (Coursera)

Bienvenidos a este curso de introducción al Lenguaje de Modelado Unificado, o UML por su sigla en inglés. Este curso surge como respuesta a la necesidad de los ingenieros de software de desarrollar la habilidad de abstraer y representar en un modelo problemas o soluciones. Esta habilidad es especialmente importante en el mundo del software donde las tecnologías son tan cambiantes. Un modelo te provee una forma de comunicar y validar un entendimiento, independiente de la tecnología en la que construirás una solución.

Sep 28th 2026
4 Weeks
Approximation Algorithms Part II (Coursera) Coursera
École normale supérieure

Approximation Algorithms Part II (Coursera)

This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques.

Sep 28th 2026
4 Weeks
International Cyber Conflicts (Coursera) Coursera
The State University of New York

International Cyber Conflicts (Coursera)

By nature, cyber conflicts are an international issue that span across nation-state borders. By the end of the course, you will be able to apply the knowledge gained for analysis and management of international cyber incidents and conflicts including for activities such as development of policy related to cybercrime and cyberwarfare. Management of cyber incidents and conflicts requires an interdisciplinary perspective including an understanding of: 1) characteristics of the cyber threats and conflicts themselves, 2) international efforts to reduce and improve cyber security, and 3) psychological and sociopolitical factors.

Sep 28th 2026
5-12 Weeks
Ethical Issues in Data Science (Coursera) Coursera
University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.

Sep 28th 2026
5-12 Weeks